{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "48fbbde9",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import Ridge\n",
    "from sklearn.model_selection import train_test_split, validation_curve\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.decomposition import PCA\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cacf305c",
   "metadata": {},
   "source": [
    "## 载入数据集\n",
    "\n",
    "以 8:2 随机划分训练集和测试集，以42为随机种子（使得结果可以复现）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "66dc5409",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude</th>\n",
       "      <th>latitude</th>\n",
       "      <th>housingMedianAge</th>\n",
       "      <th>totalRooms</th>\n",
       "      <th>totalBedrooms</th>\n",
       "      <th>population</th>\n",
       "      <th>households</th>\n",
       "      <th>medianIncome</th>\n",
       "      <th>medianHouseValue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-122.23</td>\n",
       "      <td>37.88</td>\n",
       "      <td>41.0</td>\n",
       "      <td>880.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>8.3252</td>\n",
       "      <td>452600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-122.22</td>\n",
       "      <td>37.86</td>\n",
       "      <td>21.0</td>\n",
       "      <td>7099.0</td>\n",
       "      <td>1106.0</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>1138.0</td>\n",
       "      <td>8.3014</td>\n",
       "      <td>358500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-122.24</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1467.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>496.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>7.2574</td>\n",
       "      <td>352100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1274.0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>5.6431</td>\n",
       "      <td>341300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-122.25</td>\n",
       "      <td>37.85</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1627.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>565.0</td>\n",
       "      <td>259.0</td>\n",
       "      <td>3.8462</td>\n",
       "      <td>342200.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   longitude  latitude  housingMedianAge  totalRooms  totalBedrooms  \\\n",
       "0    -122.23     37.88              41.0       880.0          129.0   \n",
       "1    -122.22     37.86              21.0      7099.0         1106.0   \n",
       "2    -122.24     37.85              52.0      1467.0          190.0   \n",
       "3    -122.25     37.85              52.0      1274.0          235.0   \n",
       "4    -122.25     37.85              52.0      1627.0          280.0   \n",
       "\n",
       "   population  households  medianIncome  medianHouseValue  \n",
       "0       322.0       126.0        8.3252          452600.0  \n",
       "1      2401.0      1138.0        8.3014          358500.0  \n",
       "2       496.0       177.0        7.2574          352100.0  \n",
       "3       558.0       219.0        5.6431          341300.0  \n",
       "4       565.0       259.0        3.8462          342200.0  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names = [\n",
    "    'longitude',\n",
    "    'latitude',\n",
    "    'housingMedianAge',\n",
    "    'totalRooms',\n",
    "    'totalBedrooms',\n",
    "    'population',\n",
    "    'households',\n",
    "    'medianIncome',\n",
    "    'medianHouseValue'\n",
    "]\n",
    "df = pd.read_csv('cal_housing.data', header=None, names=names)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "4cfe8eb0",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df.values[:, 0:8]\n",
    "y = df.values[:, 8]\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42, shuffle=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eef12fb9",
   "metadata": {},
   "source": [
    "## Ridge 回归模型定义\n",
    "\n",
    "Ridge 回归的目标函数是在均方误差（ $MSE$ ）的基础上添加 $L2$ 正则化项：\n",
    "\n",
    "$$\n",
    "\\min_\\beta (\\cfrac{1}{2n} \\sum_{i=1}^n (y_i - \\mathbf{x}_i^T \\beta)^2 + \\lambda \\sum_{j=1}^p |\\beta_j |^2)\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c59903cc",
   "metadata": {},
   "source": [
    "## 自定义 $L1$ 范数系数\n",
    "\n",
    "`scikit-learn` 中的 Lasso 以  \n",
    "`(1 / (2 * n_samples)) * ||y - Xw||^2_2 + alpha * ||w||_1`  \n",
    "为最小化目标，其中 `alpha` 即为数学上 $L1$ 范数系数 $\\lambda$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "bb9953b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-3 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: #000;\n",
       "  --sklearn-color-text-muted: #666;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-3 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-3 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-3 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: flex;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "  align-items: start;\n",
       "  justify-content: space-between;\n",
       "  gap: 0.5em;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label .caption {\n",
       "  font-size: 0.6rem;\n",
       "  font-weight: lighter;\n",
       "  color: var(--sklearn-color-text-muted);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-3 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-3 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-3 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 0.5em;\n",
       "  text-align: center;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Ridge()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>Ridge</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.linear_model.Ridge.html\">?<span>Documentation for Ridge</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\"><pre>Ridge()</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "Ridge()"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = Ridge(1.0)\n",
    "model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9552db27",
   "metadata": {},
   "source": [
    "## 可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "0e06d095",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "860ed0f8",
   "metadata": {},
   "outputs": [],
   "source": [
    "pca = PCA(n_components=2)\n",
    "X_pca = pca.fit_transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "8e7c1743",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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lwtraGtlslsuXLx/Yi3Cr0EajUR555BEmJye5du0aL7zwAlNTU0xMTByJw8RRfl6xWIxHH32UWq3G9evXeeGFF5icnGRycrJr4XRakdVBxpIEonX/BGL1gLDdGPjjtj06C4MPPc/D8zzeeecdKpUKmUyGc+fO0dfXd2Rpvv1wUp+DEIJKpUIul2N1dZVYLEYoFGJgYIDJyclDv+9210cymeSpp56iVCpx9epVFhcXOX/+PKOjo4eOVI5r/yiZTPLkk09SLpe5fv06i4uLXYE97chqKzsNgAxE6/4IxOqMc5zjN/bitCIrIQTVarW7YANkMhkuX758Yi7eGzmJxcUwDHK5HLlcDtd1GRwc5KmnniIej/P+++8fqzBnMpmuw0THFmlmZobBwcED/+3HXeyQTqd5+umnuxZOCwsLZLPZYzvebuxVhRiI1tESiNUZ5KTGb+zFSRdYtNvtbtNuJ8330EMP8f777x+5n9xBOK4Ci04PWC6Xo1wuk8lkmJ6epq+v78j+1v3uIXUcJvr7+1laWuLTTz/l1q1bXLhwgb6+vgMd77ivT0mS6Ovro7e3l9XVVT755BNM02RpaYnh4eETuz9c1z3wWJJAtA5PIFZnhE6ar9lsYpommqYd+/iNvTiJyMpxHAqFArlcjmq1SiaT4fz5890F27Zt4PQLHI6KjqP78vIyKysr6LrO0NAQly5dOpWocSuyLDM2Nsbw8DALCwu8++679PT0cOHCBXp6evb89ydZRt4RWCEEn376KXNzc10Lp2w2e+zncdD+rp1ES9O0YCzJPgjE6hTZbgz84uIizWaTK1eunPrFe1xitXFfplAodJtYH3rooXsW7M5ncJpidRSR1cbBje12m2w2eyQ9YMeFoiicO3eOsbExbt68yeuvv05/f/+efU+nNdI+HA7zzDPPcOfOHT7++GNu3LjBhQsX6O3tPbbP97DNyLsVYgSitTOBWJ0CG/ehttoe6bpOo9E4ExfsURdYtNvtbtOu67oMDAzwxBNPEI/Hd3XSgNOPrA5zfM/zKJVK5HI5isUiPT09jI2NbXJ0P27u93PTNI3Z2dluuftLL73EyMgI09PT20aCJ92gu/GYGy2cFhYWeO+990gkEszMzByLc8f9OmdsFK3OQ2sgWjsTiNUJ0Sk33zhldzvbI1mWuyayp81RRFaO47C6uko+n6dardLb28vMzAy9vb37zvfD6UdWB6HVanWLJSRJYnBwkGefffZU52EdVd/T5ORkt4R8uynApyFWW0VjY1S40cLpqJ07jsrmaatomaa5yXcwEC2fQKyOkZ3Gb+y2D3UWeps6HLbAQghBuVwmn8+zurpKNBrtetUdtPm08xmd9meyl1h2RDmXy1Gr1ejv7+fSpUtkMpnvqsUmHo/z+OOPU6lUuj1anSnAnYrF04qsttKxcBofH+86dwwMDDA9Pb2nhdN+OGpPwo2i5bpu9/0D0fIJxOqIud8x8IqinPrC3OGgwtlqtbpNu57nMTg4yJNPPnlfT7Mbb+DTYqfjby2xj0QiDA0N8fDDDx+ZI8RZJZVK8fTTT1MsFrsl5B37ptOIrHY7Zse5Y3Jykhs3bnQtnKanp+/L8eS4DHQ7rSkbRUtRlCNv+n/QCMTqiDjI+I3deNDSgFsjir6+vu7G9lHdyGdBrDbSMcztOGkMDg7yxBNPHJs57P1w1IMJNyJJEv39/fT19XUHKgLdB7STWlT32xQciUS6qcy5uTleeOGF+7KbOm63942itXUA5Em2sJwVArG6Dw47fmM3HoTIqpPm61TzxWIxBgcHjy2iOG2xAn9h6ohyqVQinU6fipPGvjjiz8p2PfI1k7blEtUVBpIhNGWzzVBnoOInn3zC7du3ee2115idnT32kSRwcLuleDzOY4891rVw+va3v83k5CRTU1MHKnzpRDzHTSBaPoFYHZCjGr+xE2c5smo2m92mXSEEAwMDXZeF4+Q03d8bjQb5fJ5Go8Hc3BzDw8P3NRfr2BEWklgCJBATCO5vMa21bV69WWKpZiA8kCQYSUV4/lyGRHjz8iHLMtlsllKpRF9f34mMJIHDG9lutHC6du0ai4uL9+y/7cZJiVWHzoMwwOLiIq7rdgX2szBLKxCrfXLU4zd24qxFVpZlsbS0RC6Xo16v09fXx+zsLJlM5sRukE5kZdgujieIaAqKfHxPk7Ztd3uims0myWSScDjMc889d7afYkUZ2VsB1lN/3jxCHvf/9yHOWwjBO7erLFbajKUjaIqM7XosllpENJkvzNzrbNFJ/01PT3d7tI5zJAncv5FtOp3mmWeeoVgscv36debn5/flkeh53qZKyJOg83c2m83u1sNnZWpxIFa7sHUf6ijHb+xEJ7I6jRLgDkIISqUShUKBZrNJq9VicHCQRx999MRvTgDbg3eX6hTNJo4HqYjKpcE4Y+mjW/g6qc3l5WWKxSLxeJyRkRGy2Szlcpn5+fmzK1TCRhI5JNHc8gsTyZtHluxDvW217bBUbTOQuJv20xSZbCLEUsWg1rZJRjZfDxuv25MYSdI55v0u0hv331ZWVrh+/XrXDWNoaGjb7/6kJhRvRyeq6xzfdd3vetEKxGoLJzV+Yyc6aYXTEKtms9lt2gV/lEQmk+Gxxx470fPYiCcE16sSrttkuDdJTJcoNixeulHmC9MSI6n7S8d1GpVzuRxCCAYHB3n66ac3lTafhT2zHRE1ZC8P7JQ6tolHVkE0gdSB3tr1BK7Hpv0pAE2VcAyB421fIbn1uj3ukSRHOSKk0xeXzWZZXl7m2rVr3Lx5c1sLp9MUK9d10XV90/l0tii+W0UrECtOZ/zGTmx8UjqJC62T8ursy/T19XHp0iXS6TRLS0uUy+VjP4fdKNQtCgZM9cmsNUzqhkMspNAwPT7O1Q8lVq7rdoslOo3Ke6U2z5xYCRdJ5JFEbeeXdCoBEcjiNngSyHv7+3VIhFV6wirlls1A8q5bRblp0xNR79mz6rDT/bKfkSSeJzAcD02R7hHJ3f7Oo75XZFlmdHSU4eFhbt++zUcffcTNmze7la7+uZ6uWO02S6tTkfzdNLX4My1W7XYbz/OoVqtIkkQoFDqx8Rs7cfemPb59q402QGtra8TjcYaGhshms5vSfGdhnlXNcFiqe1z9tEyx7eF5gnhYIxvTaJoOT02kSEf3Tk1unS7c8SPcT6PymbvRRRNJLCMJ595fIajX6xQKBcrlMqlUqvsbvDuAA3Lvvg6jqzIPDSd55WaJ26UWsZBK03RQZJnLQ8ltxWSnjIDjeixXDXJVA4ChmUfQ7Do35653R5LYeg9XVxqUWxa6KnO+L8bsYAJd3V0QjnOelSzLTExMMDIywuLiIu+88w49PT3MzMyc2APlduxU3LGdWe7W6sEHlc+sWAkhuHTpEr/1W79Fb28vPT09jI+Pn/qX2Uk1HkdFYKPR6C7WnXTHuXPnduzmPwtuGgtrLebr4Mk20ZCKLCnUWjZt00FVJK6tNnh2cufyaMuyyOfzLC8vY5omg4ODPP744yQSiQN916ct2v5JeEhiFUncG+1atkWxWKRYLOI6Lr19vVycvUixWARgYWGB8bFxVC0P2CAP7uuQ5/tj6KrMjdUG5bbNRCbK+ezO+4XbiZXrCV6+scZr8xXqhoMsQyqi8fREmmeff56VXI4X3/mEqzWF3v4sw30pTMfltYUyTcvl2andJyOfRKGDqqpdC6dbt27xxhtvIMsymUzmWI+7Ex0B2onvRtH6zIqVJEnEYjFarRYDAwOnNhp7O46yIrDj9p3P52k2m/T39+97NPpployDv8jNFe8WDXhCom072J5L3RQkGyZvLlR5bLSH0Ianb8/zWFtb60aOqVSKyclJ+vv7D1VqfBauCwkTSdxCElb3Z57wqFVrFAoFqtUqiWSCkZER0uk0siQjyRLxeJxCoYBhGLz9ztuMjIwwNOQhKw7II34t+h6MpSOMpSP72kfd7jU3C03+4OMCpuMS1hQcR5CrGvy/1wqMpsOMj46SqmtEby5jFJfIt8uMDI8QToS4WWxyYSBOJrZz9HuS+7uapnHhwgUmJiZ46aWXmJubo9FoMDMzc6Lej/czS8t13QdyltZnVqzAbw5sNpsoinJmepvg/iOazmKdz+cpFoskk8luZdtBNrRPO7JyPEG17RBRoWIL6g0TkJAlf42tGw4fLdcp1E1G05FugUgul0OWZYaGhpiZmTmSculTi6yEQFMq6EoJSQwA/lThThSFBH19fYyNjxEO7bx/d/HiRer1OgsLC+Tzed/9PWsjKeMg7U/A97OwbScc7y9VKTZNZrJx1PWWg5btslw2uJpvMJgMU2m7TI0OEteGyOdXuHbtGj09Sexwmprh7CpWp7F3FAqFCIVCzMzMUKlUePHFFxkZGeH8+fMn0oN30B6v3caSPCii9ZkWq1gsRqPROJNidZjzqdfr3abdzmJ9/vz5Qz/xnb5YeVTbNnUbJPxIS5ZAVyQ82W+QrBg2r356m0mtRqPRoL+/n4ceemhfkeN+ObVqQGEiiWV0pYLw4hTXfIFq1Bt+tDg1SU9PDxI7j1cR3D3vnp4eHnn4EYrFIou3F1leXmZiokiq91Ek+WhKybf7nFZrJpoid4UKIKop2Ovfr6rIhDWZpunSEwkxMjpCf7afxTvLLMzPsxA3GIrP7jic8rTaPDzPIxwO8/DDDzM1NXUkFk77Za804E5sF2k9KFOLP9NilUgkumJlWdbe/+CEOIh4bhzq12q1yGazR7ZYn3aBxe2SQTykktChbAlYX5QblkdUk+hRbKxWi09ut3nueyYYGBg4lr2LU7mB1xt8W+0mrXaLaq1KSA/R39/P+fPn0dT9/Z0dser+DRL09ffR29dLPpdn7vpHRJfvMDrxOXpS2fs/7W2EIxXVkADT8brpWtPxkIC+RAhFlpjJxnnpRolq2yYZVkFWUZNZnstmibG240gSONrS9YOwMaLrWDhVq9WuhdPU1BSTk5PHMrvssGLV4UEUrc+0WHXSgKqqnrnIareIZuueTE9PD6OjowdO8+3nPE7jcym3bG4VW3zzagFPwLmUylwV2o6HjH9zxWRBWNPRQxEGR/oYHR091nM6KdEWwsax71AtLVIoFGi326iqSn9/v18AtEMUdVAkSWJoeIj+bD9LS0t88sHXifVcZnrmkftKm24nVo+Opfg4X6fcspAlf3E3bJexdIRLQ74N03R/jIbhMFdostBsoyoSo+kIz0ymSUUndh1JcpzVgLuxXfqxp6enW55//fp1FhYWDmThdD/HPgwPkmh95sXqLKYBtzsfIcSmaj5FURgcHDyyPZntOI3Iym/4LVFq2bQsl3LLwbI8pmIejuUiZAVLKOhhnZZQEI6gbtqUmtau+xr3w0ncsEIIKtXbrKx+QKlcJB6OMTzQTyaT4dbNW35bxREJ1UZUVWViYoLBwUEWFm/z0kvLjI5e8qO3Q0Sp24nVdH+MP3ahj3fv1KgbNkLAUE+UL5zvZSDhp/ZUReapyTTT2Th100FXJPrioa6t1k4jSUZGRs5EZLWVTCZzj4VT53yPQmTuN7Layk6ipWnamRlL8pkWq0QiQalUOnNitTGy6pRe53I5DMOgv7+fK1eukEqljv0COo1qwKsrfol0NiKoiBZ3KnUUWSC0EM9M9/DW7Tqe59GfCBHVFNJRDV2W+ShX5/Pnj2fQ4XHuWfnf7xIrhQ9xvQq9vb1cunSJWDSKLMko93nY/Z63qoeZnD5H31CTmzeWeOGFpUNHBFu/A12V+fxMH1P9cYoNE0WSGOoJM5AMbZsyTO3QN7fdSJL5+fltj3kS7FXksJOF0/T09I4WTvuhY2JwHCa6uxVinLZofabFKh6Pc/v27TMpVtVqlWKxSKlU6vaA9ff3H0v+e7fzOEmxqrcMPlnIUa9VaXg2qWSSixNZbuZKFAyJZs3G8QQ9YY1kSGUkHWYiHUFTZVbqFi3LJRY6+5d0x3txeXmZtdJt0r0Wo6NpUukJlA1P3Z7wsPzE530fc6eoTAhwkPDW7ZpisRgPPxKjWlG4fm2ZhYUFLly4sO/FdcepvYrMZG+Uyd77L+/eOJLk9u3bfPrpp9y8eZNYLHYiI0k67DcVt52FU8d3sL+//8ACsNGj9LjYKFqe550J0Tr7d/YxEovFuqXrjnOvG8BJIoTvPNDZh1IUhbGxMS5cuHBsab69OAmx2uimsbJapNmM0JPOMDGQQZEVxj1BrVplrSRIhVWi2RiJkIrrCZIhhUxMp24e73d3VJHVZh9Cl6ERnYmp7K6lzgIPS3AEcnUvHhIOHoJ7v+OelMszz46zsiJx7do15ufnmZ2d7VoN7Xi+J1iZ13GXWFpaIhqNnthIEqAbeRxEMDZaOC0uLvLhhx8SiUQ2WTjth86D9UnN0jorovWZFqtEInHqfVamaXbLzQ3DIJvNkslkiMfjTE1Nnco5ddho/XTUT3GtVqu7cHeePL/n+WfpXbN553YNV0gogJAEa4ZgIKHw/bO9fJBr0DJdEmGZfN1ioMeh1LQ41xclqh/fzXtYsfI8j2KxyPLyMuVymd7eXi7MjpPsaSHt0w1dILCEwEMgH3DfarvzFgJcJNwdzW/Xz11UGBiIMzjwPSwu3uGdd94hlUoxOzu7oxicVhn50NAQly5dOpGRJHDXDu0w94Usy0xOTjI6OsrCwkLXwunChQv09Ozt3XiSYtVho2i5rsu1a9eYnJwkGo2emGh9psXqtAosXNelWCySz+cplUqkUikmJia6DgvXrl07dZsjAFfAmgHXV5u+H19C37e56HY4jsPicp5P5nNUag1GBzJcmr1If19v92KfVV3KLZvrhSa243Wq1Tmf1glrKlOZKFdXG9QNh5rhMLfa5Hx/jMtDB7NPOgiHed9ms8ny8jL5fB5VVRkaGuLixYtoehXXK3LwWElgCQ9NUg43TnH9T9gtmtoOTzSQpEWmpiYYHR3lxo0bXTGYmZm5Jyrcr6iv1k0W11rUTYdMVGe8N0I6ergCmc7D1MaRJNevXz+2kSSdY8L9peJUVeX8+fNdC6fXX3+dvr4+pqend40MOxPJT+OhoDMA8ubNmwwPD3erBk9iKsVnXqw6peudUSDH9WF3jFTz+TwrKytomsbQ0NC2U2fPQlqybji8crPC+yWJ+o0Sqqow0hPimcn0jm7b2yGEoFqtksvluHp7lfmWBuEEyXQ/t4WKWpPpSQtC6t3PXVUkEGA4HhFNJhWS0dbXhL64TkhLkqsaFBoWz06meHgkSfyY96r2swg7jsPq6irLy8vdBuVOMQxYON4Srte6r/OwhQuHFCwXCcdzOWhRoRBtbPcmqja5SQw6vU/nzp3rVg7u5x6aX2vx6s0SLcslpMncKDaZKzT4/HTfJnf3/bK1GjAajfLoo49Sq9WOZSRJ55hwNPtGuq4zOzvLxMRENzIcHBxkenp624b+k55QvN3xge6Ikq0DII9LSD/TYtVJA24cy3HUBQymaXZnRJmmycDAAI8++ijJZHLHL/S0R9sLIXhvqcZSxSStw1g6BJLCYtkgrNX43Pm9zTs7f3cul8O2bXr7B3DSk/T2KIykwsiShGG7XF1t0BNRuTKcxBOCNxcr3Cg0GU2FCWkyNcNhMQe3aw7jlkNMVwkpMroi8/xUmmen0sgnUBW5E52HkOXlZVZXV4lEIgwPD29qUHa9NVxvBfYZzezFQQRLCIEnBLbAL6I45EclhIXj3EBVJ7tiUK1WuXr1Ki+88ALnz59nfHy8K1aW43Gn0malZiJLMNwTZiQVwfEE79+p4grBZF+0e463S20+XK6STRyu4GA70djPSJLD0rk/j3JRDofDXL58mcnJSebm5njxxRcZHR3l3Llzmx5oj6sScL9sTEN2plR0xpIc5yytz7xYNRqNIxcr13UpFArk83nK5TLpdPpARqqnPdq+ZjgsVwyyiRB1GYQn0HWZ/rjOUtWkZji+y8AWOvszuVyOUqlEOp3m3Llz9PX1ka/btD4tdIUKIKwpJEMat4ptLg4mqLRs7pQNBpNhIpr/OWWiOkMJlYohqLQdig0L2xX0xnQuDyWOXahg+wIL27a7bu6GYWzr5i6EjeMtIUTjyM/JFi4CBXWPP99FwpYE3hEIpcDFdm6hKmMocpKenp5u79PVq1dZWFggHo8jazqv3Cxxo9BElv09svfuVBlMhumL69wutTmfvRsxSJJEb1ynULcoNW0KDZObhSaOJxhNR5juj90zkXjTee0RzWUyGZ577jlWV1e7xSIzMzMMDg4eWmw6qcfjiCA6wyrPnTu3KZ05NTWFruunLlaO43TTgR02/ndnllZn5NJR8ZkWq04aUJbl+45mts5LCoVCDA4OcvHixQMbW552ZOV4AtsTaIrv3O0Jf6HTFBnHcHDczQtfp4qx06w8PDx8T3rT8Sw8YIM9HK4Q1E2HxbJF37yGLEsYttcVqg7xkIIquTw+muS1+TJrTQvDcXnxhseFbJzLQ4lNvnPHhRCCcrnM8vIyxWKRRCLB+Pg42Wz2nsXD9Sq4Xo6dJ/jePw4uQiho2/zpYj2acsRRH9/DcReBYRQ5s6mXaGlpiU8++YRVQ6agy4z3p4iFVJYrBtfyDV5fKDOZibJSMxF4zA4kURT/5D3hF5K8tVhmsdwmqisossTbtyssVwy+90Lfjunn/RQASZLEwMAA/f2+Y8enn37KrVu3uHDhAn19fQf+FE7CNSMej/P44493LZw66cxYLHaqE4A7YrlViDr/fVxmAp95sTJNE9u2D11kYRhGt2nXtm0GBgZ47LHHdk3z7cVpG8gmwyrJsEqlbSNLdy+8StsmuT4htjNhOJfL0Ww2yWazuzYrpyIqUV2lZjj0RDRcIbi+2uCj5QZ9cY3rhda6Y4VNX1wjGb77JN22/afzP/ikwFyhSUxXaJoKTdOl0rJRZYnLQ0dbquwJwZ2ywZ2KQblao1T3+NaLL6PiMTQ0xNNPP73tHDAhXFxvGU9Uj/R8dsLFj7C0DdGFCzgI5CNKO96LwHGXEMJGVXwneEmSGB0dZbVU4cUPisyVlvnkThFHjVFuOyiyv49huR69cZ2Pcw1SEZ3hdATXExTrJr0xnVzVYLgnTHj9gaU3qjO/1uJWsckjo9tXyh1kr1mWZcbGxhgeHmZhYYF33333QJV4HU5y8OJGC6dOj1bHIu40IizHcXY97nE10H+mxSqZTAJ0KwL3W9TQSfPlcjkqlQqZTKab7jqKi+e0m5Q1ReahoQSv3CqzZkC6ZbNm+Nsdw2G4+snHFItF4vH4vkeP9EQ0ZgdivHe7StNyaVouH+Ua9Md1HhtLkgxrtGyHQt1krtDifF8Uy3W5utLiVr6N8AToNSYyETRFpmk5LFdsZAnmCk2m14cEHgVCCN5erPDGjRVq1RrtdhPblYhkB/iBRyeIh7dPSTleE8PLowljP2OijgxPuNgoqJ7AlSXcDdHUcdplud4qAhtVHqFpuVzNN/jdT+p8UIJopIeGZZArlrCFymQ2hutJrNZMZgcSNE2X95dqWJ7frzTYE6Y3prPWsrpCBSDLEtGQQq5q7ChWh7FbUhSlO0zx5s2bvPbaa2SzWWZmZnYcRrr1mCcd3WQyGZ599lk+/fRT7ty5w3e+8x3Onz9/ZBZO+2U/2yXHUWTxmRarzkW5n/L1jVVtq6urhMNhBgcHuXz58o6jCw7LaUdWAGPpMGvNKHM3IFdukg55ZLwaLQuSg4M7Rha7ca43QqVls7DWplA36YvpPD7W003vRDWVkXQEVZG4tdbi3aUqDcND8aBluSi2jWm7hDUVgaBluVQMm0RYw3S8IxGrVqvFhzdu84cfrxDVJCb7e4knBrl+/QY1L8RC2eChoc1iJYSH4RWwvAoAHio67jFGNvfiIDCFguY59xRRHGc5seeVaTsWL9+IMldoU2i5RFSFctvBdRV6exKs1dssFWr0JUKkMmkalsPsYAzXgyfGeoiHVEZSERbLbeDeSMlxxSYB28r9pOQ0TetW4s3NzfHSSy8xMjLC9PT0rvf1aYgV3B0am0qlGB0d7Vo43e8e3EE4rYjuMy1WiqIQjUZ3bQxut9vdpt1Omu8wY9EPel6nKVaW4/HqrRKvXc9TansUGgWaqRizlyd4/uLhnuKWqwavz1cot2zflNd0aFoupZaFokhE1xcjVZZIhVWKdZOesMZDg2FW1ypcLbqYjkfDdIjqHq7wcFyB43q8r1X5008MctjL2XVdVldXyeVyVKtVWnqadN8Al8d6kZCwHT+Ci+kyd8ptHtqQcnREm7abx9swwVeAb7YrcSKCZaPieBJIHaF0kLp9XMdvRJyvFllpWGSiY1TbHrYASQhKLQvTkVFVDYRKSHKoFVcw40lS4Qyfm+7jsbFU930GkyESYY3VukV/QkeWJOqGgysE45mdm3uPwsg2HA5z5coVJicnN5XlbzeSpHPM09o38jyv27s3MDDA0tISV69e5ebNm4e2cDoI+xGroHT9iOk8pTQajU1jQhzH6ab5qtUqmUyG8+fP09fXdyIX6GmlATtFIi9/vMj/78MSTVeiaspImsZySWblvQqmEuHpidSBeq1Mx+OthSpN02UgofHeUoNczWC5alFrO1wYiDHdHyce8m8Aw/bwhERUV1EVmYiuENcg13ZpWS4NyyUeUrBtgSTDasPklVsV/vOHstwuGyyUWhi2x2AyxGRvdNvKRfALQzqNu+FwmOHhYa5cucJ8xaZws3SPn57ria53nxAC01vD9EpsJwgCMIVCSJKQj6nIwkPCFqovh92mXzCFioaDY5oIccyRlZApWRKeZNFyFmi5FlFNZzId8wt1XA9VlohoKqMDGRqtNoVyjazcIDwRwrQThNYfVHoiGk9PpHhrocLCWguQiGgyj470MJ7Z3lPwqH3yOkUNu40kgdMVq41isXEP7vbt23zwwQfEYjEuXLhAJrN3i8lh6IwQ2Y1ArI6BjotFb28v9Xqdjz/+mEKhQDgcZmhoiIceeujI03x7cdJpwI7l09LyMoW6xWuVCKteGE1TMYwmiitQ8bhdafPyjRKeEHzvTO++3SxW6yallsVAMsQLc2tczTeJ6TIRVWalbiLLEqWmzcXBOFeGE8ytNik0TJYrBjXDRnb8YYtu0xeMsCpjOgIkSGgyrhDcKLZ49VaZG4UWkgS6IrNUabNYbvOF8xl61kufO4Uhy8vLtNttstnsPQUx2bhETFe7Y0ckJGzPF93xTARXmLTdPK4w9v5sPRldAkU6WsFyhYq1TdOU67qsra1RWC3gtuskE9Fj2bcSAlxJxUFCU2Q8D2pGi7FMhbVGH64niIfV7pDFc/1xFEVCD4f5z2eyhJwm//a1q2hv3+LRC+M8PT1MJqYz1RejPx5ipW7iCUE6qtEb03dc/Dp/21EvjruNJOlMIzit8vHtijsURelaOM3Pz/P222+TSqWYmZk5UOHIfo8fpAFPGEmSUFWVv//3/z6FQoG/+Tf/JiMjIzzxxBPE4/FTs8M/idL1rQMcw/Ee8nI/zWSI6wsrlNs2ibCLDPREVJAVSg1/vvxyxSBfMxlL7893zRNgOoLXb5V5904dRZLQPEEyrOAKlaguE9ZlLg8luDgQ55VbZcpNm5AmY9oebcNGcl10RcVSJFTF73tSZAnTEbRsh+srDaKaQjahdysJPaGzUGpzbbXJdFKwvLxMoVAgHo/vOqwyFdV4ZCTBe3dq3Fpr4XouFQue7osykjZoOqV92xUhgSVkdCQU6f5dSYSQsFE3xWpCCJrNJoVCgVKpRDQSJTuQJZ2apZC7TaPR4Pr160xMTByJ7ZCHjIXSDSj74iHiIYWFkkNYcYlHV1mugWGG6U/oKLLMWDrCVG+U6WyM5arBYkkwPXOB8toaf/T2dT6dz/Ejn7vEcF+KeFglvs/I/SidJLay00iSCxcunGg14FZ2EwtVVZmenmZ8fHyThdPMzAzxePxIjr9XNeBx8ZkUq3q9zv/9f//f/M7v/A5zc3PIssyf+3N/jpGRES5cuHDap9fdszoO+6fOAMd8Pr9pgOO7OYPqSp2BhE5UV9AMh5bp+nmlLU/mHhIta/9imgorrDVNPl1poCkSIUVGCFhrOoxnwqQiOj1hlWxcZ6liIEsS45kIa02bimFRMz0qLUEsCmFXpmW5vmAhIcsCx3W5udamP65zru9uush1HexWlRfeWqDV5zE8NMRTTz21r5t2diBOb0xntW5i2Q7JmsPDYw0czH3/3V0ksJDQUFE5vGC5QsFG7iYdHcehVCqxurqKZVndWVgdix5FUegdHKGwWkQIwTvvvMPQ0BAjIyOHXmwcoWILaVO1YzykMjuY4L07VRbrHmFNZrKvBkLHdVTCmkoq4kdZn+QbLFcMLg7F0RSZ/uQoEyNZ3r52h3//rdf5/KW9ixs20hGr43yw3DqS5MMPP0RRlBPPuHTwPG/PwZhbLZxefvnlXS2cDsJe1YDHZVt3qEeDpaUl/uyf/bP09vYSiUR4+OGHefPNN7u/F0Lwy7/8ywwNDRGJRPjSl77E9evXN71HqVTix3/8x0kmk6RSKX7qp36KRmNzp//777/PF77wBcLhMGNjY/zqr/7qPefyr//1v+423j788MP83u/93qbfb3cus7Oz/NZv/RZ/6k/9Kb7whS/wl/7SX+JP/Ik/cZiP4ljY6HZ+FDiOw9LSEm+++SZvvvkmlmXx0EMP8fzzz3Pu3DkcSeNOxaAvHiKsKfTHdTTF36JvO9C0PCzbI6wrpKIaksQ9jbu7Hl+ApkjIkoRpu6zUTAoNC4HA9aBtueiq/97llk1fTOehoQQjqRCSAEWWSIUhHVYxHBdXCCTAdFzqbQfLhXrb5tPVBh/lapQqVebn5/nkk09o1JsMDWT5/Oc+d+Cny764zqXBOKMZh2i8gCuaB//wN2ALf4/poAjAFioWMt76KJlbN2/x3nvvsVZcY3BwkMcee4yJiYl7FiJJknBllamZS1y+fJlarcbbb7/NysoKQuz/+vKLRvy039Z1KF8zuL7awPMEsuRP34roMsOZOrYos9Lw06W6JjO32uBGoUFzw1iXkK4zNTbM8PlZTNPkhRdeYG5ubl+tJCcx26lDZyTJF7/4RWKxGNVqlbfeeot6vX7sx97IQdJwHQunz3/+8wC8+OKLfPzxx5jmIR66DnH8o+TAd065XOZzn/sc3/d938d//I//kf7+fq5fv75p6Nmv/uqv8lu/9Vv8s3/2z5iamuK//+//e7785S/z8ccfd10NfvzHf5xcLsc3vvENbNvmJ3/yJ/npn/5pvva1rwFQq9X443/8j/OlL32Jr371q3zwwQf8+T//50mlUvz0T/80AC+//DI/9mM/xv/0P/1P/OAP/iBf+9rX+KEf+iHefvttrly5suO5aJrGK6+8Qjgc5lvf+la3dN2yLM4CnQvhfvLiHbeFXC5HoVAgFosxPDxMNpu956nMcj0s16MnrCJLEhcG4qw2LCptm7Zl47gemi4xFNNRZZmBuM7gAQxHDdsjrvuNxrcrbWxPYDoCw5Jo2y6z2TiPDMfJRDWiuoLleAz3hEmEFLLJMJNJicVCDSWioykWrufier7ThgDCqoQsQ7Nl8Oond5jpgYtjvfRmBym2PR6dTB3qc6y0DN7P32SlvsZCRaAuVrkwkKA3dvhUmoOEEBr6PseDeMiYQkV1BSsrKxQKBWzLprevl8uXL+97BIaDTDiR5qGH4pRKJRYWFsjlckxMTOw5sNBFwRYS2xkLti2Hj3N1GqZDKqYz1aNhIVM3/So+RW0TlWwq7TSyLCHLEuWWzXyxxWPjdz9H03bpjUUYGXuIodEG8zeucfv27T1HwR/XntVuqKpKJpNBlmXC4fCJjCTZyGGKOzoWTlNTU8zNzfHCCy90Hen3itK24jjOrq48Z8bI9n/5X/4XxsbG+Kf/9J92f7Zx7pIQgt/4jd/gl37pl/iTf/JPAvDP//k/Z2BggN/93d/lR3/0R/nkk0/4/d//fd544w2eeuopAP63/+1/40/8iT/B//q//q8MDw/zL/7Fv8CyLP7JP/kn6LrOQw89xLvvvsuv/dqvdcXqN3/zN/mBH/gB/tpf+2sA/O2//bf5xje+wW//9m/z1a9+dV/n0rFcOu1G3I1s9Co86IXUKbXP5XK4rsvg4OCeqa9ESCUZUqkaNv3xEBOZKJWWP1eqrvi2SBFVZiYbY3YgzmOjyQP1NEV1habpUDcdkmGNatvCcPwZTYbj4SEYTYVZa9oYtkvVcLi2WqfQtEjoCtWGR90WGDULVZFwbZCEn24KSQLX9ZCES0TVSCfitCIR2koMyxRM90eZ7j9YPxhAw6rx6u2rFBptUmGFkAzFhkXbqfHkWE+3YOMwuIAlNDTsXZuHbaFSrjdotlpUqlVisRiDg4PdhXI/bCyucISEQCeT6SWTSZPP5bl+/TrxeLw7m2jzv/X3x3aLv9ZaNjXDIRvXKTUsZBn6IhorbagbLq7r4Yoa7y59gsIw6ZhO03J5faHMeG+UVFQjXzWYX2vRsj3yNcNPK45fZkJuMbe+TzQ7O7ttSXanbP2k95c7qbiO8exxjyTZyP1ENolEomvhdO3aNb797W8f2JF+P2nA4+DAsfO/+3f/jqeeeoof+ZEfIZvN8vjjj/OP//E/7v7+1q1b5PN5vvSlL3V/1tPTw7PPPssrr7wCwCuvvEIqleoKFcCXvvQlZFnmtdde677mi1/84qYv/ctf/jJXr16lXC53X7PxOJ3XdI6zn3M5CwMYt9IxhdxvGtB1XfL5PO+88w6vvvoqtVqNmZkZPrfP1JeuylwcjGM6guWqQcO0aVku0ZDChYzK44MRHh5OcmEgznNTKdLRgy3UqYiK7UHNdGnbLoYtQJLQVZmoJlNr2/ybd3P87ns5rq42cTyPG8UWNwstbpfbLNcccg1Ya1hYtoPrgu2CYXkYjkBIEgOpBNl0ipnBFOf6ojw5keL7Z/t4/lyG0AGEVQiPtrvCYvUWxWaboWSIiK6gKzAQD9EwXPK1w6dQOriAhYYQ9y6ylu2wkFvjnQ8+ZO76XNfX7tKlS4drn9jox7h+XFAYGh7miSeeIBqN8v7773Pjxg1s288ueMIvotjrCnQ9f2HSVIVMXMd0PaqGS8vyMByHStum2rZoWnVM7zbxkMREbwQEvLNY4Vahyc1CC12VGUuHycZD2K7gjcUKLSXB5z//ecbHx/nwww95/fXXqVQqm45/FD1Wh2FjdNNxoX/uuedoNBq88MIL3Lhx49jG/BxFGq5jQvz444+zurrKCy+8wPz8/L7WnAcmDXjz5k3+wT/4B/zCL/wCf+Nv/A3eeOMN/uv/+r9G13V+4id+gnw+D8DAwMCmfzcwMND9XT6fJ5vNbj6R9dB642u2TsrtvGc+nyedTpPP5/c8zl7nEovFKBaLZ0qsYO+KQLG+d9ExkNV1naGhoUM7akz3R9EUiblCk/m1NpYruDQYZ7Vg4uF75X2cq3NxIMaF7P73fVqWv7iHVIm26VA3fL9BXZVRZPA8QaFu8e25Muf6olweinMhGycb1/iP5SKllk2ladGyQVZcPMcf9e4Jed38FOKqjIvEat1EkuD/c2WAR0aSB/4M/AbfHJ6wMexOlZmEt+FJMazJ1NpHswh5gLmhibder5NbLVEoVYnF/bRtOp3mxo0bR/qk3jluCBtVVZmcnGRwcJCFhQXeevttBoYmyA6PdE1mdyMRVtEVP507mAixFJZZarqUm65fCCIJxLqDcdNucrs6x0B8ki/M9CJJcHEwAUj0xXXyNYtC3QT8toT37lQ51xdjYmKCkZERbt26xRtvvEF/fz8XLlwgGo2eiKHsdmxXDXicI0n2OvZh6e3t5bnnnqNQKHQd6aenpxkeHt7xGHv1WZ2ZNKDneTz11FP83b/7dwF4/PHH+fDDD/nqV7/KT/zETxz5CR43iUSC+fn5TU3BZ4GdXCwsy+r2CRmGQTab3XM+1n6QJImJTIRkWMVwPD5YrlJsWMiOoDfq7w0tVwzeWqjuW6xWaiavz1coNi3WGhY1w99r0lV/k94TfvGGJwSa5aIpErbjUahZrLUs6oZDy7CotD1/FpOjIAO6LGN7/qKr4Rd71A2beEhFkmC1YVFuWaQiGrYrKDQsHE+Qiqjbpu+EEDTdCm23giY7SPjnKASbhMp0XRqmy3DPwVz0d8OybfJra5RXc1gupHv7uPzQ/vei9mKnlIzftKwRknyhDIfDXJi9yFq1xc35eZZWVhkfH9/TDSEV1hhLR7hZbKGrEnHNb6UWAlRVRlckmqaLIoPjQd0yeKSnyFgmTcNQ6IloeEJwo9ik2LCIrTeGr9UtTLvKH5vtJx3TUVWVmZkZxsbGurOexsbGyGazpxJZCSF2jC6OYyTJRo66x0uSJLLZLP39/eRyOebm5roWTgMDA/ec826RlRDi7BjZdp7eN3Lp0iX+n//n/wFgcHAQgJWVFYaGhrqvWVlZ4bHHHuu+ZnV1ddN7dMpwO/9+cHCQlZWVTa/p/Pder9n4+73OJRaL0Wq1znRk5XkepVKJXC5HsVikp6dnx9EUh6VhOrx9u8rHuTr/6dMiyxWDkCaj41IxFJ5M+wtPrmZi2O6uXm0Atuvx1mKVqmEzkYnQNB00RcJ0fDsnCQnD8XBcf2xIZxjjctUgVzNomzZt06Vld4ZsKP4iKIHt3fWMkGSw3fVN9rAgpim8uVilZbn0xXUsx/P3xYQgqqtc6I/y8EgSZX2kiCMsqk4Bx/PTX6anYlkmtbZDpW1RaFj0xzUW6nDrZgVdlUlFVdaaYXpjGobt0bZdQqpMVN/fd9GJiguFAuVymWish/TwebKZJPvssz4QOzbUAobwfQyRJCxPIp5M8vDDD7O2tsb8wjyLS8tEM0NoEd8ouD+uE9XVDe8N2USItYZNrmZQantoqoKgU6UnIUkCyxHoin8NybJHzV6gNzZONhGiZbnkqgaZqI7peCgyxHUFw/HI1QzSGwpaOrZIExMTXLt2jbfffhs4+dTUXuXjRz2SZCPH9bduLNHvjHvpWDj19fXddfV/UNKAn/vc57h69eqmn127do2JiQnAL7YYHBzkm9/8ZlcQarUar732Gn/lr/wVAJ5//nkqlQpvvfUWTz75JAB/9Ed/hOd5PPvss93X/Hf/3X+Hbdvdi+Ib3/gGs7Oz3eql559/nm9+85v83M/9XPdcvvGNb/D888/v+1w6AxjPmlgpikK73ebGjRvkcjkkSWJwcJBnn332vvsktuJ6gjcWqtwsNvkk38CyPVRFRpLA9SSW6y7SQoXxTJSw6vc57SVWa02LYtNiKBlCliQqbYf+uI6q+MUVkiwh1kVHlkCWwXNdqqZF23IBBSRQVXCc9XYv/O0XwV2xshwwZJdkWKXYcAgrbYZSYVRZ4uWbZRQZvnC+l4jmV6i9c6eGpspcHIhjiBpNt7zpSbDSdnjvdoO2aZIMa9wstHh/qUa7DX2STW80xK1iC9vx6I/rVNoOhuMRUmUGEyEuDMTRdkif2bZNsVikWCjiuA59ff3MPvQ4WsiPomwEknCRpZNzLxECGp6OJovucSVJoq+vj7Yc5vfeWWDh6jyhkMpwpoepbJLHxnroi/up5lvFJp+uNLBd37GiYnjUXQlFlmlbLtb6A4krvPW0IHy8XGM0Y5MaXaLc1tFkuFlo8qlbx3Y98CQSEYXHx1KUm9tX6CYSCZ588knm5+e704pnZma6DhPHzX5TcUc1kuQwxz4sG895cXGR999/n3g8zszMDJlM5sFJA/78z/883/M938Pf/bt/lz/9p/80r7/+Ov/oH/0j/tE/+kfdE/25n/s5/s7f+TvMzMx0y8WHh4f5oR/6IcCPxH7gB36Av/gX/yJf/epXsW2bn/3Zn+VHf/RHGR4eBuDP/Jk/w9/6W3+Ln/qpn+IXf/EX+fDDD/nN3/xNfv3Xf717Ln/1r/5Vvvd7v5e/9/f+Hl/5ylf4l//yX/Lmm28e6FzOmlg5jsPq6irtdptr167R39/PpUuXyGQyx3YTFhsWS5U26npZ8WAqhFuGcsvG9Txk4E7VIBlWmR2I7SlU4JeVe8L37qu0bdq2Syamr1srmTRNF3tdI1wPXMujvr4VZHoKugwhTfEXrw3ee96WDIMHGI6H2fTbZcu6wnDaL5EOKRIeUG3bhLQQNcNhrtDkTqXBo5MuY70KQz2hrgegQHCz2KRuOvQnIhimieW5GI7v5BHXVUKajGF7fJpvcDukMt0foy+mYdi+5ZMArgzfNbrt+C0WCgUqlQqJRILRsVGSyQyOpCI2lYNLvgEunIhguSg4QkZIYArWXTb8e2CtafGfrq6xaiik0ynWak3eWyiyWKxj2jZfvjJE2/K4vtr0I66ERst0KBkuDdev3HI9gev5Po+aLJEMaaiqhKLI1Noud8ptPsx9zId3JJYrChFNIR5WkTV/COe11Qbff7F/178hkUgQCoWYnZ3tptxmZ2c3RQLHwUHLx+93JMnWY59EZKMoClNTU4yNjTE/P89bb71FOp1+cBwsnn76af7tv/23/Lf/7X/Lr/zKrzA1NcVv/MZv8OM//uPd1/z1v/7XaTab/PRP/zSVSoXPf/7z/P7v//6m2vx/8S/+BT/7sz/L93//9yPLMj/8wz/Mb/3Wb3V/39PTwx/+4R/yMz/zMzz55JP09fXxy7/8y92ydYDv+Z7v4Wtf+xq/9Eu/xN/4G3+DmZkZfvd3f7fbY7Wfc4nFYpuqAY+r+3o3OuNHOnZAkUgEXdcZHR1lbGzs2I9vOB7ues+SYXuEVAkkPx2jyRIhRSArCo4nsFyxr+q6dERDkSReu1nG9mC1ZtIwHcpNi4bpcXfYsB9FCdmvSmw7/gB2WQHXFbRtwV4ZcE/4/0/IUGpZqLLv3o4kIQOG7bJQajNfbCGkJpLepGKGKN0BIZKMpPxrwXQ8yi2HiK5ws9BivtTi9poFnh8CNkwXF8nfh1mvluwY+sbWa1pyNZPJ3gghWVAsFCkUC3ieR19fH1euXCEUCuOi7ti31BEsbYNw3A/bXs9C4KDhbKlEtISMhoQqOdxYbbBUalM3HPKmgytkPFlnqWbxjffvoDttLkwM0nY8hmMhbMfj2kqDugW2cHE8/yHE/+4EjgvxkCAb1RlI6rQsQa4uMFxBy2sQj+soXpqwpjCQCNG0XMoti5a9+2fQ2TvqOJB3IoFEIsHs7OyR++J1OKyR7WFHkmzkpNNwGy2cbty4QbFY5NNPP2V2dvbILJz2dR6H+Uc/+IM/yA/+4A/u+HtJkviVX/kVfuVXfmXH12QymW4D8E488sgjfOc739n1NT/yIz/Cj/zIjxz6XJLJZHe0PexvsNhRYZomuVyuO2V4cHCQJ554gkQiwXvvvXdiVU4xXUGWJZbKbUotm1zNxHE9Py8vS7RcSMYkZgbiRHVlfZrv7tVpuipjOuuVgJpCWFdYKDWpth0QoMtgAwJlPd0IDcvDWRcxwwZvn/577oZpGI4rkIGIriBLwi+TlyVylSbReI2226Q3HqIvprPWtJkvtRjsCaFIfnwlAfOlNncqhl8UYgkUZGQkik2LlAeqKmE7gqgm+9OK2xaegHhIoVpvcW2ujNuqokTiaIksih6lrkjYDUGPkIiG9vpeJWyhwBH5CW7EEzI2ylYHrS62kLBdhXfvVLlVamJYLiChKRLJiIYry3iS4OPlCo1amaaWQiR1qm2bfM3EEWA49/rQu0CpZSIQqKrKWlsgYZCM6LieR1j3B2zeKSeomw6ZqP+wc6vY4upKg5FUmHjo3vtyY+m6LMtMTk4yMjLSjV4GBgaYmZk58tT5/bquH3QkSQchxKmZ6Oq6zvT0NAsLC+i6zssvv7xjM/SZSAN+t9EZEdL58o9brDzPo1gsksvlKJVKpNPpbacMn4SZbYdMTEMC3l2qISFwHBfD9UuObVkQkv2S7bnVBpWWxRenM3uK1UrdRHiCbELn1mqVStOgZXjYnowsg6rIKJ7nu3cL35JJAjTJX9jcvcKpbXDXDXPXmjYh1c+be8KjbTdpiBy6Q7cQomm5RNbFxrBdYrpKSFWI6jLXV5u0LZdyy8b2wEZGFgqYHrZrIEkyfXGNhunyyq0ydcPv/xKOQyYClx/K0I5Ocadus7jYpmU1CWs6mXiY3oTNlaEE/fG9n6JtISPu8xbd3BSs3hNNbcd8uc0nKyau649EkSRffKptm7CmEA2p9GTSZFMSHy+s8HGrTjiRomH5PXA7fXWmC7m6R77VQJIkQrKMrpnUTRfXE6hyi1DEpGH2Um/bSMArN0pcXWkw3R/jv3h0kKGezYvidqXrnehlfHyc69ev8+KLLx55s+5RCcZ+R5JsPC6cjL3UdnTWpCtXrnDu3Dnm5ub4zne+w9jY2LE3Q3/mxarTFCzL8rEKRKcnKp/Po2kaQ0NDzM7O7mhbcpIDGB1XYLkeqiwT1VVcT2AbDjbrqRwZmobrT/ktGXzt9Tv82DOjTPXuPGOoWK7x0eIKjaZBOqLQ1x+n5pg0HRtVAsXP0oEEwvP3OKK6hK7INEy320O14V3ZPm3GPa+6U/ZTfrMDMZLxBmvtKkpLoMq+W/tiqY2EX6k2mAxtGnUSD/lVaA3LQQj/vDzAkxQMDxTXQZI8orrMjUID27LRZf8Bx1JVbFUn78RomDZN08V1JRQlxGrTxRYWSDLXVpqkoxrqPhYcR8jYnrZjJLQfBDKWp+17DOTcahNkGUWL4FltBKBIEm3LRVNkMjENRZEZymYY6MvwxrUlbiytUqxLODucpyckLE/1v3QHZASu4mI4fnWnvxcpQHaQ9SKlSg+6ohLWZMKqxDu3q7ie4C99YRJlw/e1W9o+EonwyCOPMDk52RWC8+fP7ygEB+Go51ltN5JkZmaG4eHhTX9fZ306rfEkjuMgy3J3FuCjjz5KvV7vRofj4+NMTk7uasd0WAKxSiSwbRvLso68yKIzOymXy9FsNslmszz88MOkUqk9w+STjKxMx6Np+o/E2bi/p3Cr0KLUtrFc38xWMh1kWULxPF66VcF0BX/2mVFmsnc3h23bJp/Ps7y8zFzRoGGFGBvsJRQOcadioMr+07Ll+o29iuT/b+hUBUqYzk5L6t5iJeGnF0ttmzcW86RTbfoTCg8PJ3hoOME7t6tENIVURKXteBQbFomQgut5dGrGdVVZ3/OSEaqHYwmU9Z4wgYQnFKKKQ7Xmj2DviWmoahRNVUmEFSqGzfvLdS4PxFksOxQN8ISfystVTTzhl/VfHIzv22PQRcIW2n71ehOeULDE3k4UG2maDomwiqZILJddEBaSJNAViVhIIRXRiesquizTnwqRfvwcc/kqX3v1FjXTZasxju0pOMh303WsPwC4d6s7/XPtGPy79KYqmEaafM2kJ6ox1BPm2mqDW2stpjf0+e1HNDrNusVikatXr7KwsMCFCxcYGho6dLrqOIYvbjeSpFPu3ul366wJpxlZbc08JRIJnnjiiW50WC6XSSQSO7zD4QnEav1DPaqKQCHEpp6oRCLByMjIjrOTduIkI6uwJiMBLcshpocoNEzqltutvBP4i4gi+bOkFPzqwNfmy6SjKrLVZHl5ufv3jo+PMzSd5KMXF5mvmngVm5WaSaVtb0rvOeLu+isBDdO7e7x7znL30ELBL393hcCV6lRcC9FSWWv6zcwX1vfbJCBfN1ElifFUGF2VKTRsBpMyhbpFvmrgCb/Uuvv3C79SUF4fFh/SNBQNkpEQ09k4juehSn6VW8t2aZounqSy0mxRbTvoqv/5IoEnPAp1E9PxaKw7j8dCyj1TibfisT8/we6nJcD2VGxkDqpwA8kwH+bqjKUjSECxoSJ7Jpa427LgeB4f5GpoK37vVSysMz2UYfn62t1z9iR/fwx50xlsvKo3fqtC+N+hJCCiQSJSQ5bDFBoa46kotutRbm02AD6I3VJfXx+9vb3kcrlu5eBh+56Oc1LwdiNJotEos7OzaJrWjWxOg92KOzZa6AV7VsdANBpFkiTq9fp9iVWr1eoayAohGBwc5Omnnz5wWWoHWZax7f05c98PNcPmpbkSN4tN1lo2xaaF4woc199PkuiUIXvYDjiun8Ir1S3mlgr8p/ICI1GPoaGhTX9vtW2jqwq267Jas/0obT1HJEu+UzqShGl72C73PfhdAEJyiMXrqKpD0/SFS5Ul2o6/J3JxIEbNdP2BjgIczySmK5SbJrmKwWrDpFC3MG3fFV54d0csdpb8cEgllYyiKxIKFq7wCKnr+52eh+1IxMIRbpYMCnUTw/GIaDKGLXDxsB2PWFjhg6UqkuQv4pmYxkBSxxN+mrInotETUe8RMA8JC40QDruJtydkbKH44nqI9OHFwTgf52rka+a6e4REsQbZKDw5nqBt+9V9uiqzUjH4jx/lMWyPdFRFldb3ID0ZB4WDCKWAbpVo0/KIhSTU8BprLQfHFfRGdVJbfCkParfUEYJO5eC7775LKpXiwoULJJP7t+g6ibH2nZEkIyMjzM/P8+abb5JMJk8tqoL9DV48rvP7zIuVLMv3lK/vF9d1WV1dJZfLUa1W6evrY3Z29kCu2DuhKMp9zZzZDw3T4Xdevs3rixVqbRvDcmitF5/J+KIC60/1HqiKQFMkHMvGdA1WqmG+d3qEzz00fs/fa7sCGcHtsrnJS0/gL2ZNW6DKAsvjQCmqndBDLWKxu/OmLA9sw/XFVoKm4ZuqOq7A8TzkdSNdaT1a7IuHSEdUVmsmY0mFT1ctDM9DRl5vSJbRFZAlmbbt0heLYNoS80V/6KMkQ7ktoek6yYjKp/kGLdvFccXd2U2ShO1YhA2Z+Xib2YE4FcPhrU8rtG2XgWSY/rhOMqwylYkyPRDbEpP4Tui5pqBQrVMzbKK6wkgqTDauAxIe/sypjf/soE+5qajOVx4e5LVbZRZKbXrCIR4Z7uGhoSTv314jX62TCKssllvMF5u+36PsO5C4AixXxZPu7/r38FsFJElCiCJm02a4Z5T+LYU9h2016fQQdSoHX3311e4g0v1YXZ2EWHXolI6PjY3x8ccf4zgOH3zwwYmNJNnISVZLb+UzL1aSJBGPx2k0Gui6vqdTcqfJs2MgGw6HGRoa4sqVK0daCXMSe1ZvzFf49lyJStvCcgUbW1p889q7/y0EGJZAUQWJqMLF4TSOJ9O7gzCXWhYfLteptZ1uafrGh3zHgx23pw6AJHmEYi1UxfYjwQ3rVied6AlwbEFz3VFcBlQJ5PWpxZ+uNHk+rJAr1Liz2sARENXAQ8ETAlf4qamQImG5fjn/SCqMYTncqUjUTQddDzGa0bs9aIPJMJYryNUMHA9UGUKyhOF62K7HzWKLhuVgWALDcbFdQcNwiGkKUU3m1fkKtysGQz0hvA0fVKFh8v5SnbblkAxBzTBZqVvMZuOM9ib37EnbLwPJMP/Fo4M0DIeGYdOwXK6uNLi5ZpIMhUC4XF9pUDdsFEXC8wRty6XpauycpzzYppvAFwVVkelNGGihGnXDIRW9e5/dr2jous7Fixe7lYPf+c53mJiY2HPO00mKVYdQKMTY2BjVahXP805sJMlG9tPjdVwpys+8WMHd8vX+/v4dBcI0zW6az7IsBgYGePzxx0kkEsfy5ZzEntV7SzXWmr7Jq+eJHSu5Oo27DiBpKul4GMeTSUYUercZFyKE4I35Mvm66e/3iKOJnrai6hahSMuvKMSvNtNkpxsR7oS//wOSI7Adl7bl8rLZYro3BGoETVVIKg6tmoXWmYwrPHpjGg0bRlLhbiNxPBLG8iSeHY+jKfDW7SqJkErVcEibKstVf9KxwJ/d5bKeRm3ZOJ4H+BFePKQS0xUqbb/3a61p89YiJMMqKcXiS5pD/4Dg1lqbluUQ1VWatktU1XCF4NqaRW/Sn/Hlew82qNfrRKMHf/I2bJfbpTaL5RZXc3VuV9qUWpbfMK7I9EQ0NEXQtPxIynEEjqdgC3kXoYK7QuWxn+lEEtAT1ZjsjRHWZNp2jZvV24ymL3TvuaNq4u+M+ahWq137pk7l4HaidBpi1Tmupmk8+uij1Gq1bpXjQWdSHZa9rJaOk8+8WHVKMJvNJoODg5vEyvM81tbWyOVyrK2tkUqlmJycpL+//9hLR08isiq3/blVALa3m1PE3ZvSMB3uVExcoC+e2HYI49WVBq/cqiKEuO+9qG2RPMLRNoq2eU9PSL5g6fsQLFhPSeKLad1TWbE0bEDxPEotB9Px0BUJSUh4HjQsl8y6VYXtgJBVYmEFs2UjyRqK5K2PdpfIRHWu5hsIz7ec2vjc4XrQtl1UWeCsl21nYoKeiEK+ZrJU8cfAK7LvQr/qOnCjzviITbFhstawWHIMPCFhewo9YYlE2KPSNMGoUigUcByHeDxOLpfrXkv7uWYtx+PdO1XyVYM75TYfLFepG866Az20bI+K4dAb07A8FSEsDE/1HYX3rRn7HBwJRDUZXZFpWw7llkOpVaVs50hpA8iScuSi0ZnztLVycKtj+mmJ1cbv8aRGkux0/O04Lsd1CMQKuOsP2BkT0mg0uj1RHSuX/eayj4qTiKwyYRXbE3ib9o12T9U4gOV6tCwXRZH4KNfge+N690ZuWS4f5xto66mho0ZRbULRFpK8w3tLEranoskusrTT8Tc/2fv9XhL5mk1Ul2jbHoblocqdcnXP32ezPAZ7FBRJxRQK6vrvZAkkWULXdaIhnZrh0BvVCKvyeirLj6YEIAtfID2xngaVwLL9FGChbrFUNbA9QViV16s0JRwPbpVMbpfaFBs2ZcOhLxbBkxQ8T7BSa5EvNuk1lhlMRRka8udgaZpGoVDg1q1bvPP224yNjzMwkGW373elbrC41sITgrlCk4bh4HrrhTaSBELgelAzHCxXwnBDaIp30Ir6fbNSM1EVBdcTmI7Lcs1ktVHFi7uktcFjsUfbWELecUzvVA729vbied6pztHaKhbHPZJkr+NvJUgDHiOxWIx8Ps/Xv/51nn76aW7fvk1/fz8PPfQQ6XT6VMpEDzIp+DAIIRC2sS5UGxfv7f5WD7843G/g1WTfty+syORqBuWWTWa9Z6jcsqm2HcIK1KyjFCtBKNJCDW3vwr3plZKE5SlokouyrahtXmRkCTIRX2RMRyAEhDWwXBlnXXBl/L/5TsVhMKWhKn66rdS06U/4RRGyJDGeiXM1X6XYMImHZDRV9nvH1pufN5fDS0ieIKRIqKpMqW1hOX4RS1iVURUZhD8Wpe0If0KxBK6rYLlgmk0ajQY1QxCNhDg/Pcl4/93qU0ny9zl0XWdycpKFhXny+TyTk5M7eubdKbW5XW5TM2wKDRNjwxauhECW/TL+lqXgIuFJ/ueky86x3Cc100OU2yDBYEKnYVhcX2mQimoUzBVM1zy2+1OSJEZHRxkaGmJ+fp533nmHdDrN+fPngdPpddopojvOkSQbOS3HdfiMi5XneXzrW9/i448/5pvf/Cbnz5/nqaee4nOf+9yum6snwXGlATt7bzcWl3hv3kGXwfD2f9O5+P1Rlutyq9iiJ6p2F3Twe2tzVYOba+0jO2dZcQhH60j7mFzbRfJ7fBA2yh43j+uBIzxc4aHJvkDZviWeP3xR+KNSPElB8QSVlkWuaiKEIBPTmB2I+1EHMJyKoKsKxUabqmGTiRpU14tMTFcg3LsGSur6QEJZwo9YXLrViwCm4yIEmDZoip8y1CQFyWkxv1xFURTC4SjjQxHiEQ01HF2PKjcXCcmSRCaTIZ1OkcvluXr1KslkksnJCcLhjdkCwUrNpNCwEJ6Hs8XzSgC2C5an+otS5+eShCVUNMndZ4JvN+7dz/LnhUnUDZcbhRYgM9GXouU0Waqt0q8kj9WAWlEUzp8/z9jYGDdu3OD1118H/Cb4kyps6LBXZHMcI0m2Hv+k/+YOR/Jo8D//z/9zdxxHB8Mw+Jmf+Rl6e3uJx+P88A//8D2DEhcXF/nKV75CNBolm83y1/7aX7unGu9b3/oWTzzxBKFQiOnpaX7nd37nnuP/7//7/961+Hj22We7F9Nu5/K3/tbf4vz58/zoj/4oiUSCH/uxH+Pf/Jt/QyaTOXWhAo7UTaPjR/j+++/z8ssvUyqV0NLDaIkUEf3gl0DDcKmbLnNrTRbW2mgb3kKTJRqmQ6m1dwS0NwI93CaSaCAph4kyJWxPw91DjD2g3LTRVL9gJKLJeEL4QyKFQKDgCAVdlRlOhtBUmUuDMZ4Y7+GpiRSpLdOH++I6Fwd7+P6LQwwmwyTCKoPJMNmYTkiVuntl4EcLEV0ByY+mQqpf2l8zHEzLxbBcXASWo3BtMU+rXCAVlnjy/CCPnR/iyliGwWSY/phOPKTiCj8Nut3WgSTJDA8P8/jjj6HrOu+++x7z8/Pde67QsCg2Tb/oZJtSTduVu5ZJHReKDgLfAPf+M7+d72rzG0U1f75Zqe3yUc7gOzfXeGO+zAerbV5cXeXVhRzuMaSdN6LrOpcuXeo2vr700ktcv359zwrio2S/e4+dkSTf+73fSzKZ5LXXXuPdd9+l2Wzu+W/v5/jHuWd132L1xhtv8A//4T/kkUce2fTzn//5n+ff//t/z7/+1/+ab3/72ywvL/On/tSf6v7edV2+8pWvYFkWL7/8Mv/sn/0zfud3fodf/uVf7r7m1q1bfOUrX+H7vu/7ePfdd/m5n/s5/sJf+Av8wR/8Qfc1/+pf/St+4Rd+gb/5N/8mb7/9No8++ihf/vKXN00i3u5c/vk//+f82q/9Gnfu3OH7vu/7SCaTKIpyohfebhxFGrAzvPHll1/m6tWrxONxnnvuOR5//HGiyRSlprmLvdHOuEDT9Cg3LT5dqfP7nxS7hRot28N0PN9d/T6QZZdIoo4W7vSa7edS3eZvkSRsIe8pWG3b6+6xeZ5AkX0/OxcNIfk3Z0yX16fWSoymwoymwoR3GZeSioW5POyPvagYNlXTQUJCU/wRJp4Hpi3QFIVMVENTZfpiOmK9MtNwwXAkTFcGWSJvaMxOTzKQ7ceVFDRVxvb8zu1zfVH0dcsoV0jYQkWIjWZGd1FVjdTAKH0TF1guN3jjrbd55ZMFXrtVIlc1MB1B3bz7/XmA6Sq4G4ooNPVez41O+vUwJsT3cvfdHQ+KDZtc1WW14bBca1NqmAz2hOmPKoRVmbfyi3y0urLL+x0dHd+7Z555hlKpxAsvvMDCwsKJOM4cdPBix9T3i1/8Iqqq8tJLL/HRRx8duodzr6bg49wyua80YKPR4Md//Mf5x//4H/N3/s7f6f68Wq3yf/6f/ydf+9rX+GN/7I8B8E//6T/l0qVLvPrqqzz33HP84R/+IR9//DH/6T/9JwYGBnjsscf423/7b/OLv/iL/A//w/+Arut89atfZWpqir/39/4e4A9tfPHFF/n1X/91vvzlLwPwa7/2a/zFv/gX+cmf/EkAvvrVr/L1r3+df/JP/gn/zX/z3+x6LkNDQ+i6Tjwe7xZTnIUBjHD4AgvXdSkUCuRyOSqVCn19fVy8eJHe3l4kSaJpOrx7p8prtyoUGvamPYmD4IFvvSPg5ZtlRlNhPn8+w51ym7lCi/vRKi1koIeNLdtn+7kJdriJ1wXL80CT7/1Mu43DlrsuUgKEgun6aU1d9VN2Eqw7Kezfay8dDxPVw4CJJjloikTNcFEVCVWWaNkusZCKLEtEVRkXqasvjifhoRBSIarLlE2JctvhyfEUy1U/vZjQZVRVYbVhUTVssvEw/XENb33MiBAdx2Afw/H4cKnKSs3E8QSK0kubKPm5FRJhhb5InELDv478XjgJZ0tJuir5kY653YOdhD/eRHg77BceHN+V3x9U6dh+u8Fa068E9TwPXfEjupdvL1Jum6S1FIM9YbKJ/c2HOigdx/VUKsUzzzxDoVDYVDk4MDBwbIv2Yd3eDzuSZCv7aQo+rr/9viKrn/mZn+ErX/kKX/rSlzb9/K233sK27U0/7zTevfLKKwC88sorPPzwwwwMDHRf8+Uvf5larcZHH33Ufc3W9/7yl7/cfQ/Lsnjrrbc2vUaWZb70pS91X7Ofc4nH44dysDhOOpHVfsPqRqPBtWvXeOmll5ifnyeTyfC5z32Ohx9+uDs11bBdXr5Z5p3bVSzXJazJ99X/ZDtet3bwTsVgtW7y1u0qa03zUNVhkuQRidfRI1uFajsOeOaShIuCvU2Epa1X88V1GYSEi07bk7uu8N56Wb/l+HN9J/siu0ZUHSzXo9a26UuGMF0ZD4EtfBsoISAT9Qs1IppMKiQjCZtKrQ1IOK5KSNM2zHCScDyPO2WDiK7w8HCSx8d6cIGlsm/tNL9m8NbtCjeKLf8TEv7+0sZpxHMrDe5U2qSiGiOpML3xELmmQO/pY6g3hVGrYpkmnidhdSyTtiw+miIhS9IurQ7+fqFzgL3QnbA92U9rrv8N7nrP3p2Kwdxqg8WqwycFi1durvH/frrKN67d4vfnrvONT1b4JFe77+Nvx8YiB0mSyGazfO5zn2NqaopPPvmE1157jXK5fCzHvt/Bi52RJE8//TSVSoUXXniBW7du7Xvd2+34QoizWbr+L//lv+Ttt9/mjTfeuOd3+XweXddJpVKbfj4wMEA+n+++ZqNQdX7f+d1ur6nVarTbbcrlMq7rbvuaTz/9dN/n0hkTcpbEqnNB7PYk5ThO19W90WiQzWZ55JFH6Onp2fbp5k7F4E7VYDwd5ZrTQFf3Kynbv65mevRYLvGwiul43KkYXF1pdgbrHoiNDb7bs17n3X3B4RZCFwU2RFhRTUKROhGEguVI2K5vsBRdF3NVlnEcB12V6I3rzGTvFlTsRstyqa1PIpRkCVnoCM/39bM9//+E57JWt/DaHqgaih5C8QQSfjm4IoGFn15VFYXVusnLN8r0JXQQUKhbDPeEu993w3C4tdZmMBmiJ+o7cFieH2EZjkO+ZpCKaF2nDVUCXZMxbJdQvIeePplhUeWDFQdvh8/YcgV2eyffyrutDw4ywgXtEPuNHuKuSK1/1LK07srueaxW23ywBHHZpWwKSgZEdYVczcRL+pHwe0sw1BO5x0/wftmuIq9T2NCpHHzzzTfp6+tjZmbmSKfpHjQNuBP7HUmylQeuKfj27dv81b/6V/nGN75xLHNLTpqO3VKnz+ossHFy8Uax6tg9LS8vs7KyQiwW6xpz7nURlZoWqiRRbtvcKRus1PZbBLH9xSvw+2CKdZPZbAxVlig1LGzXQ2G/5rQe4di9Db5bX7PbeRwUFwXhSuiKixASmqqAJOMPMfZLx3VVQZMlJFn2pyUbDumoylRflL59jvZQZYm64VA3XUZTEXJVE8OWSIagbphU6w6qDLKqEOuJg6RRrtrIsoMsCRwhcB0P1wVkQUiXGEtH0VWZxbUWxYbFaDqyaXGJh/wFu9J26Imup8EkGUuoWI7vjRjR715PkiyRCqvMN20sx8P0ZMKJFNJaxR80xeYxHnCwwZiuJCM80LdJv+5E58HhHjcMsf6IIsk0HVgothiMSdQdiWQ4RF9c9ysWHY+y0QDJI1/vIRW9/yq4jezWELzRx6+zX3zQsfV7HfuoDAn2M5JkK3tFdmeudP2tt95idXWVJ554ovsz13V54YUX+O3f/m3+4A/+AMuyqFQqmyKalZUVBgcHARgcHLynaq9TLbjxNVsrCFdWVkgmk0QiERRFQVGUbV+z8T32OpezGFl1bobOvpVlWd1ZUZZlMTg4yJNPPnmguTG66o+wuFNto8rSAaqndnnS8vwx8GOZNj94Jev3AYn9RVaS6qCGDYS03We+sTn58E+SqsS2NlKeJPtztTwPSZYxHA/bFcRDKiFVwhESsizRn9DJRHQqFRNFUxlK7v/hLB5SfRcK16MnoqFILrW2Aa5LRJMYTke4NJLCc6FsSliuy52K5R/flXE9gcB3AZGAc71RzvdHURUZXdGZL7WpG063x63zqYG/zrcdl6Wqxe2aS6rUojeiEtE16oZNKK7jeoJyy2atYdOyPG4ULVo25Ksmsiz5zc74voj3Uy7jIWN6kt+Ltcu1JPBtm1y2d8Pwo9x1k2UBIFFogSoLNMkP51uWSzKk0rYFIdVkzV7F9qJo8tFFV/txrwiFQly+fLnrOdixRJqcnLyvyOR+04DbsdtIknQ6vem1+3FdPy4O9al9//d/Px988MGmn/3kT/4kFy9e5Bd/8RcZGxtD0zS++c1v8sM//MMAXTuQ559/HoDnn3+e//F//B9ZXV0lm80C8I1vfINkMsnly5e7r/m93/u9Tcf5xje+0X0PXdd58skn+eY3v8kP/dAPAf6F9M1vfpOf/dmfBeDJJ5/c81w6kVVHrI6zZ2O/dJ5Q1tbWKJVKFItFenp67svuabgnjOkIVus2k+kwquy7k98PngDHcclVDJarBr0xDWlPL0CBEjaR16MpDxnHFaiKx90+myOKonZSzfX0mIuK7Ph7g9q6a4SmyHiuB+u2SWFNoe7A+YzCYM/Bno6Hkhr5UpXcShXXgbCmku6JEtZVLgyFGUjEWK7bXBgIMdMfpWG6zBVa9ERkmpaL5XiEFEFfVOXxkYTfKAyoikIyrFA3HRzX6/682raJhRQUCd6cr7C01qTaEDi3K6QiGtl4hFrZ/75KLZuVqoGDTF8ySssWNCwX0/Xoj4ewKm3f4eR+voDOx42E5ao7Ng939tf2HNYlIKRLKB4kQiqGZeN4kK9arNYsdE1BkgQImVQkQTIqkTfz9Ov9hJXdHzRM2+VmscX8WhNPwFg6wvn+GLHQ5mXyIFZLnT2icrnM1atXuX37NtPT04yMjBwqnXccYtVhu5EkmUyGCxcukEgkfPu0B811PZFIcOXKlU0/i8Vi9Pb2dn/+Uz/1U/zCL/wCmUyGZDLJf/Vf/Vc8//zzPPfccwD88T/+x7l8+TJ/7s/9OX71V3+VfD7PL/3SL/EzP/Mz3XD5L//lv8xv//Zv89f/+l/nz//5P88f/dEf8X/9X/8XX//617vH/YVf+AV+4id+gqeeeopnnnmG3/iN36DZbHarA3t6evY8l42j7eFoQ+3DYBhGdy7WzZs3GR4e5tlnnyUa3X6M/H7JJkJcyEaZLzYpNC1CukrrPkv1BVBoubTuVPn/vrmMQCKkgWNtL1iS4qKEDaRNaSGBhx9NqEf8sW+nVZ4HrlAQSCRDEpqqIuEy1OOPuFdlf65U2/aomQ7llk1YljiXCSHjTzP2vf2kDQUQG44pBLV6ncLqKsZKhTA66f4eIqEw5ZbjT+INaYRCcYotv/F3uCdEMqwy3R8jrCm+zZHwe7aqlRIFQ2GpZlI1XeIhhURYpSeiEdNVik27u7kd1VUu9Me4UzEptSyycRXNlBjuCbNSNQmrMldG03yyVKXYbJCOR8mmImSiOrbrsbDWIhFWcVxBpW1Rbzt40mbRl9e/rwN/F5KE5WloirMpVnY8eb3icO/3kNZzkmFNxnJ9qzDL68xcg7bj4Dgu0YhGWE+SCKt4wmPVWqVP7yOqbH8P2a7HKzdLzBWaREP+LLDX58vkqgZfnOnblDo9jC9gOp3m2WefZWVlpWuJNDs7u2O6bSdOwpNwayrzlVdeYWhoiKmpKYA918YzlQbcD7/+67+OLMv88A//MKZp8uUvf5m///f/fvf3iqLwH/7Df+Cv/JW/wvPPP08sFuMnfuIn+JVf+ZXua6ampvj617/Oz//8z/Obv/mbjI6O8n/8H/9Ht2wd4L/8L/9LCoUCv/zLv0w+n+exxx7j93//9zcVXex1Lh3X9c6XcBqhbqdxd3l5mXK5TG9vL6qqcuXKlXtC8fvhynCC22WDqCpzs9Ck3DqavrKmJfgwV+c/u9jPx7k6bdve0iAqUEIWsm5t+tnGoom7gnV8/SquK6/vpfkJKVVVUWSQUeiLhVDXx394QnC90ERCIhr2hwguVy3+zbs5dEUirCmEVJlsMsRsNk5Y84dlFotFCoUCruuS7u2jd3SSfL5NsWnhNgxUFXRVIxzSqbQdYrrCxYEog8kQkiR1G4z74iE8T1AzHVYLgprhslQxyER1lqseigQPDSV5ZipFte1QN2xUWaY3pqHIEh/nG/RGdZz1/jdZkkjHdcoth8tDKoOpGBVDMJYJdRcXXVWIaDKOp2K7grF0hAXRom5sSdNK0sEraNYREtiugia7IAkcV8WTpH0H0p7wnUBs13d8d++ZhyZRtcF0TF65tkJ/TOf5872EVIWCWSCjZ0io96bOlyoGN4stRtORrjlzr6ezsNZiodTi4uDdf3NYwZAkicHBQbLZLHfu3OHDDz8kFosxOzt7TwHYThxnZLWVTiqzU+7+8ssvA5xIP9l2SOI4aw0fEK5du8bly5dZW1vj29/+9pFEMful2fRHwnf6vIaHhxkaGiIUCvHqq69y4cIFMpnMkR3P8QQv3Swxt9rk9VtlXp6vHtl7K8CfeWaI126WuVE07hZYyC5qpBNN7T3TSEIcqoJsO1Q6Ax/9/ZBORCDhVwJmk2HiIZmG4TCajpDQYXYgjgRcKzSIaAoTvRE+vXWHgqmSbwnCisRoOkI24c+v6gvDoNqiUqkQj8Xoz2ZJp1PcLLb5ONcgHdVwPUHNcCg1XYZSEa6M+FNp4yGVsCqjKR4ygjvlNu/cqWHYLncqBoWGxWq1RUiTGcvESYQ1VFnCcT0+dz7DY6P3TretGw4v3yzTE9WxzRZrxSKTU1NYrkel5fDcVC9LFYtPVxqM9ei0HX86dN2wmV9rE9Zk6obDtdV6d7qz43p+ynfP1WJ/4z88zw+RDhskaHBPxNdBwvevlIGECo+Pxfni5RFmsgk0VSapJUlrmx8A316s8O7tKpN9m+/7pUqbiXSUL1646693584dcrkcTz/99OFOfh3Hcbh16xbz8/P09/czMzOz52Txb3/72zz88MNHuibsl9XVVd5++21UVd12JElHxMLh8LFEV59pb8AOyWQS13UxDONEiixc1+2WnNfrdfr7+7ly5QqpVGrTl3wc/oCqLPHsRIqekMK7d45OqMCv/nt7sUrb8YhoEg1bIOsWSshkaxS1G6ITYcnu3nsYu9ATknGEwPMUTOeuIS2Apvj9QpbjUXE9HM+j3HSIaiGurTRoWg6OEMQ0hav5BtfWXGqOn/4yAMNu8GneI6649Ibg+y+keOjy5a4zv+N5LFdMoiGFiO6Xjoe0ED0xQallIUkSvbG7m/62K6NKHroq0zQd3r5dxXA8dEVGlf3vrWbYJMIq0/1RPI/10R337q9GQwo9EZVKyya6oTG33LSJ6SEiukZvXMLL1XlvuYHluBiWSalpoasyl4YyrNQMPl6uAxBWZQz8xci578tRYLsKAhmEQMVDPkTzsO2/1Q5H8FODcV0mFFaYX2vgvH2NtXMDfP7SGDW7huN59OmZ7menyhLeNm/ouOKeMThHlYpTVZWZmRnGxsaYm5vjpZdeYnR0lOnp6R39905rNAlAJBJBVVWeeOKJHUeSnLlqwO82On0QG4ssjhp/IF69W3IeiUQYGhrikUce2bGD/Lic18Oawvn+GCHlaC96GWhbHqbtoUguarSFpHTr0w70Xh7+rCbtkILVE5KYHYjz6YqBLQSSBLIsUCRfqEAiFQ3RG/XdI8KqgqpIWK7AkRQGkipLlTYfrzTQ1ocnSkh4nj/V13UEiiJhyCpNOUTBiyNrd4svXA9sz0OTJFxPxhWdRdHfM3PcLd+rBHNrBtfzdfI130k8oil+ilLyrZmapsftcpuwKjOQCG3aR9mIIklMZ2N8mGuQL9m0TMHtkklI0zg/4BdppKMqkgyrNZOwJlM1wfIEYUmi2DBpWS6yApYlkHVQFQnTk5AR3ceOg16Z/lgUle61IPnuGIp3dG4XG1Fl/ztWlDAjWY2PF1ZQjTKXzk9jJVQsb42hcAZZkhnqCRPVFNaaFpmohiRJVNs2iiwxkt48Guioep06bHSXuHr1Kt/+9rc5d+4ck5OT96T8TjINuJVOj9VOI0my2ezZtVv6biESiSDL8rH0Wtm23S05NwzjQBOGNwqn6fgL1UrNRFMkhnr8abX7aU7djo9yDZQjfkKTgHLTwBAWetRC9cR9+cSJQwqW30yrMF9y/FEejoMnfA+EiO7vy8iSxJNjSXoTvgGsIsGbi1UimsKVIb/yqW64rNZMPFXCdsF2nG4aLBLSiIb89J4sS1TaDoW6yej6wqYrEomwznLVJqvdPfeW5TuHxEKbF5yG6XCj2MJFQpU14rqDrirkawaOEGiSL1qKJFFuOdiu4NJgfMdrqC+m89REimuyzS2ryfRAksFkuNsgWzMcNFnisfEeLMfjRqGJKkvYns21lQa6KnfNcC3H/x5lSUJVwPUEUU2habn7FizHk/DEdlWeEq6QEZ6HesSC5Xgeay2TTCzMUF8GoUVQwi4ffPQpqXSKiYkJXOExHO6lN6YzkY7wzp0qi2stEmGNeEjh0ZEeRno2VxEeV3QTj8d58sknNw1TnJmZYWRkpPs9n6ZYbTz2TiNJHn300WPrvQ3ECj+COUrLJSEE5XKZXC5HoVAgkUgwPj5ONps90IXWiazatssrN8sslNp+WbUQXF1p8vBwgkdHkwd+mmlZ/n5If1y/xz378Hh4koSpGmi6gyf887xf/JJnBV3Zp2Ctp/0sISOvp3Uk/BSPJkskdAVJltc9AKEnrCIhYXu+y3pcv3szhhQJw7IpNNzuRr7Aj1wMF4TlEFIVIprij6Q3bEaJrJ+3wkgqSqFZZ6VuEtUVbNcfIDiTjd1TRVhtO7Qtl76YTl5VcFEwHBdvfXRI0/MQku1/FqpMKqpuSiNuRzKkM56OobSrmwoEwHehcD0YSPrpprWW7Z+nqiHh+GNVOtZQ+O4RiiKhCAjpKomIils3aNm7f8dCgOMpmyyf7kXCE8p6Cf7RZRLalsB2bUDmndsNsskI46O9xCZHuHPnDu+++y6Dg4PUhgxWijpLZb/4xxP+lObnpjJM9UXvub+OOxXXiVzy+fymysFMJnNqQx9he6HcOpLkKBqfdyIQq3U6vVbhcPjQYmWaJrlcjuXlZVzXZWhoiKeffnrPTdOd6JjZLqy1WSi1GU2F0TpD/1o2H+bqjKTC9B/QsNPxBK4niId9k9T7NEgHQFI9QhEDRfEdIAx7ux2Aw765H2Gpkoe0y33qCQnHk9Ekif64jq4qlJs24Bu+RnWVsUwU2/Mo1G1WGyaTfVE02S/q8ISfpqvVa1QrVfJlk4rpv6ckvA0FIwLb8ZCRSYQkxtMRhPCr6fxiDt95vC8R4rFRicVym1rbIR5SmB2IM5K698nTcj3/MxPQl9AptiwqTZeG6SDwIzVNVUhHNcKaTCKsoms7P/h4QsH1fLne7mEmqsuENJmm5RDTVfzknETNcLBdl3gIYiEVy3UR6/ZZEV2mL67TFw/RG9N46YZD27Z3/J49z//s9hsV+/12EqpyRJkNCSKaiuNJvLdc5/uTYVIRDVmWOH/+PIODg8zPz/MfXnqTpprmyZHzjKaT2K7HnVKbd+5UsFwPVZbIJkIk1ys1T2LfSJIkhoaGGBgYYHFxkffff7+7XXGaacCdjq0oyrZpy6MkEKt1OuXrsVjsQGNCPM9jbW2N5eVlSqUSmUyG6elp+vr67vuC7hRY3KkYRDQFTZEptSyWKgY1w6HStkmGVb58Odv1etsP8ZBCJqYxt9okosnbzi7anbsVXxICeb3Bt9PS66cXj3bfT+A7p2vC23btc13JdyxHQkh+A3RY8/tlGpbDcE8YWZbpifjVdJWmTalp4bguwpNZrbeIeAarKxXkuEw0niTvSBiOhQBUT4b1p37Pg1jEj6bCmoKmSIRUiXRYx/aUTYu3v7jrOK5AkaV7zt1xBZ/mG3y4XGeu0ORGocVUb4TpvhgfO4JcVSEke0Q0meF0hL64TrFhIwREtvnOhQAHBcfxcBxzR2PRZFhjNBVhrtDwoywhiKgStbaD7XoIFKKaSjbuzygTkkw8pNAT1RhKhsgmw8xkLdpLFZr3TIRer7zc4vi+n0pBDwnbldGUjm/H4ZElCUlSsT0J4brkKwZX83UiIYWesEYqGmX6wkVuGLdxi0VeufYOsfAwIa2HWtumtGBxp9wmHlJJhDUeH+thJhs/0SIHWZaZnJxkZGSE69evUy6X+eijj7hw4cKJVSx3OM2GYAjECvCfYmKx2IHSgK1Wq1ty3rErmZ2dPdJ8bSeykiXfiqbcsvk418B2BTFdwfXgk3yDvrjOc1Ppfe9fyZLESE+YXN1AkQ+zIPg3qqw4qBEDIfmLlcC3X2qYftrs6JGwPRlNdrvRgvDAEfKmNJOybnga0VR6oi6Rum+nlAjJaIqEEBAPq4QViUK5Tq3eQPNMHhtI4uhDlC2JqysN8jUbIYGCjIlAcSGs+tFdWPEfHkzbZbVhIslR3l5qko5ZjKUiZLak6NQdphx/uFzjxRtlHE+gqxKllk3xtsX53giDyRCO69Fotvz9wJZDue0Q12V6Iuq96Skh02iZFIrLFApFPM9dr07cmsYStCyXid4IYU3mTrmNpkh44ItuLExYkTBcl6bpkkxqaIpMb1wjEVIJqQqOJ/iecxnWmibXVlsbzmFLEcUmNg5W3M12ScZ2pfW9yh1ftiuOK/vO+JJvm9UyPT7K16kbDkOpCL1xnXN9MUZSYULhCLHeQW4XqiwV7yA7ZWpWDE1TSYY1xjMRik2LtxYq9MZ0PM/rLtqVls2tYpOlikEyonK+P7bJWPio0DSNyclJFhcXkWWZF198kfHxcc6dO3dik3v3M3gxKLA4ARKJxJ7VgK7rsrq6Si6Xo1qt0t/fz6VLl8hkMsfyJXUiq9F0hIVym9Waie149CVCNC2HdFTjXF+UW2ttZvpj+0oHup7fvPv+nRqLJQNzfcz6zrGk/zQcVdbH2Xvr0ZRmIzQLpI4b+vqrBUcwLXY3JGxXRZVdBH6l3dYFLar76a+aYdO2XaK62vW6qxsOwvPQPZPxkMWQrPDw+T7GBvsJhTRcDxbWmlxfafhvK8BFrO9XybQdibDmEg3JxEMqpabNUtXFFQ6TGY3bpTbFhsVjoz30xjQqLYdczZ89FdcVhlIhete9/Azb472lOo4n/KZgJAaSfiRdM12+dyxF23IRdpuorhGNqEgSNC2P8AarD08ISuU6uZUC9XqNdDrN9PQ0iUScubk5KpUKt27dYmxsjFLb5fpKg6VKm4blEtcUhtN+sc7N1SZtW2C5lr+/5nqEZImG4dIbl3lspIeLQwm/wEJXiWgyL98sIdPCA7/qcV9pv/21L1jrxTVb3243k2R/j0xe3+uUkGwXRZbwhGAgphMLq1iu32330XKVWEgmrCp8WK6RSsQYTMeZX61gtMp4TpxCtcVEb5R0ROPjXJ1PV+rEXJdQKESxYfLv3svxab6O6/lp5GwizFceHuCR0aM1z4W7zjqPPPIIU1NTXL16lRdeeIHz588zPj5+7OnB03Rch0Csumx0sdgqVhtLzkOhEENDQ1y5cuXYn2gURcGyLM5lIixXIvyH5TqSgNW6XxE42RulPx5ivtSibrr078PTdqHU5t3bVX/QIIJ0RCOuC1Zr1g6CJROSYbxHRdZCVEyDitvEcP00jecpSPL9p2wOimGrKIrYdl2M6irxkErNcIiHVHqjOgKBjkO7VafZNhhORXnmwiSj2fSmU1dkf9SEh19cYG+IEAXgIGHaCpbtokbDhEN+GblvweQwkoqwUjdZKLUQXpj3l+u0TH/Bvd60ees2XBqMc2UoQd2wqbRsUhGta/AaVhXGU2EKDQtd8SMyTfYHhtRNCce10RS/rNq0LQqFErl8AZDo6+9namoKXfejOkVR6O/vx7YdWq02L7z6NiUlTc3T1qNfwc1GkzcWKmQTOobj4XqCluWhyH76zxGw2nCIhjRuFJqcz8YZXDfztV1/KrQnwBYyQsi+6+0GJPzijMNVhUrYroIqu5uahzd/5XejNK8zKHId2/OQPRnT8XulYmF/Ptidcpum6Re0tG2PbELHcT0MxwUUXDlENGUT90yuLSyi2E1MNc6dioHleKTcNk9OhHnp/Tx/+PEqkuRH6smwxlK5xb9/P8dUX4xE+GiX142RTSKR4KmnnjrwiI+jOv52HGePFQRi1WVjNaBpmti23W3cbbVaZLNZHn30UZLJg1ffHZZOZKWrMt9zLs3tssFiuc1Awh+H0BNRcTwPWZL2PZvqRrGJrsjUhEtEV1E8AaZFRIX6+s0KWyZHSVA2XMKqwUC/IGLo5KsGkiIjPEHLZn1T/Pg/F8+T1vdCwPUklC1FF6oEo6kwj44m6Y3phGWPeqXE1dtF1kyJ/mTi/8/enwdJll33ffjn3rfkyz2zKmvfe5+e7lkwAwwGXMwFImQRjiBF+ic6KJuUaMpkAIygIJuiLIuO0B9WiHLIsEmKkMI/iw7bUMiUglQEQCMCGlpYhyA5mMFMz0z3bL3WlllVuefb7/39cTOzq7qqepnpAfCTcCKAmK56lW/JzHvuOee78NSpeU5Ml6jkjv74Z2yLjVZAeMz2PdGCTuQwIywKGYt8xsaSKXt+wmxZU8hYNAcxQZQSxIqiZ3NtzyyQYaJ5/p0m/TBhrZYbq7Jn94El4lQhpcCSkomczc1tRaMTIu2YYsam6ipev1kn291kbrLA0vIKuUIRx7YOtXW11liW5Pz5R+hc2eDWmxv0Y8FEpUTWc2gODPItVmqoRZhhbxAQRBozezJgnK1OTL0Tst0N+ctPznNyqoAURqboINrv4PmHnTju3Vk/Zp4ljF2IrVNGtyaH40PzkkbiP9HDGdn+99ES5FwLz7bI2Ba9KEH1DDgp5xhUpR8r6t2IomdTybn4kWKyYPy+KjmHcKC5Uu8SRS0KxSIzpSo3b6U893aPl3faBEnKbMkjVXrM0VpvBbxZ7/GB5cq9bvqB4ih+V61WY3Jyks3NzQPIwVqtdsyrvPtIkuSuG/T3Wwzpe8lqGMVikW63ywsvvMD8/Dxf+9rXKBQKLCwsMD09/R0pf0czK601t1ohqdLs9CLCRA3t1gWNbsRMMcPMfbQAtdb4kSLjSDJSg4rQYYSroORJstqiFSgsYWZiiYYgSlFCEToRjuVQ72lsaZBiYoh7T5QiSq33OWFp0vTgbAog1RJrCLoQmJmLACbsmGCnzla7RaVc4cMX1igWywYsccz8aBSNXkijd7TXl1ICoQW1gsdyNc96p4/WZlephq2gWBkn4F6QUvJsbjZ9glgxkXfRWtMOYnZ6MTk3pOzZvL7VI5exKLg2niPpRQkrE1mmii6fu+SzNTDwcR2lDAYpO1KzVLKxJuepzJZ5uxXQabRwbclixWOpkj10j0IIlJ1lZmaW69tNNhtNesoi1PYwMRonYs+2cCwLn4SMY5GGCUJAEKeEieKlWz1a/nX+40dnWK4WaA/UkC59WFBCDP9P68OeWIfjbvMsQTJEg7qWZnEiS70T0ovUUJTYPvTaOVfy5GKZRGmKns12J8SPUjp+YpJYxiJM1BiZ2R2q1Z+o5UiUHrZKQ7KuhLJFOc5jhz1aG1cpW4LXWpK2b95Tb7jRCJOUdhAjtGAQPXxhgeMqm9HMfIQcfOmllyiXy5w9e5ZS6bAc13s5//fagN/h2Nra4vLly7z88stIKfnt3/5t/sJf+AsP1eHz3cSosrq+5/P81SauLTkznedm0+fPb7SZK3k8s1rhqeUyzn2qUWS0z2vXGhD2yEkXlfHIey5lbRj/662A5arHTMnj2t6ATuRTD7toodDaJh2qkacp2JaZT42WliS1sKV66PlKK0McPS5SJccVliU1zXaHt691OL00zfLyMm7m/tu1UaJ44XqL+M61RmvSIdJPYpLiZD5Dc5DQGoSAqUpSpeiHKaencmx0QvqhASnkXQuBINUaKSTVnMOb9T5+kpBqzXY7ZMcK8Wwjp/SRtQl2exEbrQH9GNSw8lAKVGLh+jYvbfi0QrAtSd61COOUSxtd/Fhxfnb/Z9e8IXnPIkk1iZVBZSyEHxCHIZZt05eGV1bK2rSDGIVCaQspJUGUoJQRjk20ZL0V869fqjNdbBPdwxXaBlzHItWafnQ/dIbjPjymxZeVUHBtOnZMJzBV7v5wpKnRJnMuTyxVuLbn0wtiNJrtbkCaQsmzubzdZbqQIWtLbFsykTeK+9vdEBCUsg4TBZftTkicKtYWXE4Wz9Brtbl24xbtTkLJyzMIU0qeQXo6UlDvJswUMsyWHj7f6F5uEJZlsba2xsLCAu+88w5/8id/wuzsLKdPnx7LgL2X+E63Ad81/vIf/IN/wAc/+EGKxSLT09P8xE/8BFeuXDlwTBAEfOITn2BycpJCocBP/dRPHTJKvHHjBj/+4z9OLpdjenqa/+a/+W8OQcf/3b/7d3zgAx8gk8lw6tQpfu/3fu/Q9fzO7/wOq6ureJ7HM888c8jY8ahr+Vf/6l/xkz/5kywvL7O5ucnFixf52te+xsrKync8UYFJVkmacmW7h8TAsR+ZLfL9Jyd5ZqXCdDHDE0vlA+Z7R0UYhly7do3nn3+eZOcm5VyGqfkVnjm7yHQpR9tPiBNNybN4dK7IWi2PRuMzwMqmFDMSTxr782rOIetY1Ao2YWJ2qvvbZYmS71qR+3BoA0nX9/4CpFoilMIVUMpnWT19hoWFhQdKVGCQjGbB2ncVY2KrCQHEiWarEyKFWaC2OhHb3ZCNVsjKRJbT0wWmCi6dIBlrzmk03TChmLGQAt5q9Hmr7hPE6ZCUbOSgViY84kGHz73wNrt9QwlAC9J0pAIBu/2YVzb6bDRDagWHgmtRzZp7ff6dJp97eZs/urTNn97osdFN6QUJC+UsWdeiG8QgBdVyHifjonVKEgREUcxOL0RrMzsL44RukBCnECQQpzAINC1fcLUR8+p6F+cuVaoGwhSkJfAc8Z4+Fo40GwTbctjuJSTYOEdVGRhIfy5j4ceKubJR0h+EqUn0aAZxitJQ74V87Z096u2Aat7hI2sTPLVc5bGFEt9/qsbHL8zyfScnWazmmCrb9GSHylSVbNbDsS0yYQcdB9Q7gTGx7MekqeLRhSJL1feeHO6M+1WvcF2Xc+fO8f3f//0AfOUrX+HKlSvE8d3cuN/b+UcWNe9nvOvK6ktf+hKf+MQn+OAHP0iSJPy3/+1/y4/92I/x2muvjUmwf/Nv/k0+//nP8/u///uUy2U++clP8pf/8l/ma1/7GmBu/sd//MeZnZ3l61//Opubm/wX/8V/geM4/A//w/8AwNWrV/nxH/9xfumXfon/6//6v3juuef4L//L/5K5ubmxVci//Jf/kk996lN85jOf4ZlnnuHTn/40H/vYx7hy5crY2PGoa/m1X/s1/upf/av843/8j/kX/+Jf8Od//ufk83nq9fp7eqgPKyzLIohSujKl4Jn5VGsQEytNMesQ92OCQyWACa01e3t7rK+vs7u7O0aI1Wo16r2YK/Ueu72IHzw1ScGTpCns9WOaQcQLt3bZiXsAlDM2tZzFTi9huuBiW5JUpaRKECVHG/MlSr7nCktrSNX9oZtG87VcJsPChEci4I3tAVsdw0ObK2Wo3kPtYRRSCLQWRuFCaUOsvSNZ5jOm5/j6dpfdQQJaM5l3EcBWNyCbkUwVXFYnc/SHya81CLDlyIbD4p2dAfVuhBDaqGC4YgiDD/h3r65zoyJY7wsU8shnoTDIxuvNgFoxw8pkhr1+zEYrYKcf0R7EJBpUEpITCc61Jo8tlrmwUOJKvUfXj+kmmqxjg2uTJDFdPyGfJlTyWdoBdPxkH7JTG5SdFsihXqUWUMjcHZ2ngCBMsB6AB3hnCDSeI3BtG9e2CBMjsFj0AN8QVWNlwCG2JajkXGwp+JN3dumG5h4822Ku7DGI0mGLTpCminfqPXb7EX/h3DQFz6Zyx8Zvvuyx0Q6od0LKWYd+uMNWGHNhaZqM67JV3+FGs0OqPYST4cnlCj/1gQUydyFsv9t4UE3CXC7HY489xsrKCm+88cYB5OC74Yl9p9GAD80ipNFoMD09zZe+9CV+8Ad/cAzt/uxnP8tP//RPA3D58mUeeeQRnn/+eT784Q/z//w//w8f//jH2djYGPtPfeYzn+Fv/+2/TaPRwHVd/vbf/tt8/vOf59KlS+Nz/czP/AytVosvfOELADzzzDN88IMf5Ld/+7cBUy4vLS3xK7/yK/z6r//6fV3Lb/3Wb/G5z32Of/bP/hlXrlwZuwh/J2NnZ4c33nyL3cIq13d9ru35NLohGshlbCZzDj//4SVOT99WyAjDkI2NDTY2NtBajy1H7mwDaK2JUo0URurnj6/soNEEwufFzT2COKUVGL+lDAk39gYUC3nKnk3LT7jZ9OmF6V13y5Y8msB7rxiDKI6I27MPMymxhBm4Z4bqDgCupXlkLk/Zc1BAOWtzcb7IzH20ZrSG3/uTG/zby7uEsTzy/iaytjFe9GwURr3djxSFjGSqaKGUYHkyyyMzeSMou97hi6/v0AoSPFvgWBI/Sdlsh2RtSZikJIkGUhJl4bmCj1+Y5f99o8GtdnooWe6PuaLNQjXPo7M5tno+UaLHZPG5kke91SOJfGampsi5FmdmCrxZ7xkQhxDYUpAqY4cSJymLOc3mXpe9xGGjlxKno42DODQvdKSRnkr13flQjjRv2j2UmY6NogsFV0CiyedchHTpRIqM1Az8LrlcniDRJGmKbVlM5R0WJ3Ls9CI22j6uFFiWJFWKQsah6Ue0+rHRjcQo6z++WOE/Ols7JEsFBn37Vr1HJ0gQGlrbG/yF8+dIZZWrOwO2W102tuoUrIS//KGTXDy9+lDaYVobCTApzWfm+vXr7O7u8oEPfOBdvdbOzg5XrlwhTVPOnDnD7OzsA13nV7/61bFh5FGvr7Umk8m8b4Tph5Ym2+02wNhn5YUXXiCOYz760Y+Ojzl37hzLy8vjBPH8889z8eLFA0aJH/vYx/jlX/5lXn31VZ588kmef/75A68xOuZXf/VXAYiiiBdeeIG/83f+zvj3Uko++tGP8vzzz9/3tdwNuv6dCsuyQCs8W/LCjTaDOKWatdFa0OiGpIni7UaPlQmPTqvJxsYGu7u7YyvqycnJAx+cMFF0/BjHMqTSkerFRjugFQUUi4qeH6I0zJQ8bBlh24I4MNoQgyjlkZkCvbA3HiBb3NbMuzNSJR8sYQ05MpnhLCw+omwbzYwsKShmjA26bQk8SxImikRpbM+mH2qCOMS2JB0/xrMFtUKGe432wiQlIx20OjpRSQF+nFLK2pQ8Q35VWtPxE/wYLOEhZIIj4HrTp5JzuNUyYrQVzyYFsrbAj1OiWBGEw5sU5mkmGtJQc2V7QDcQd01UYIwIb+z5+FFClCTGbkMIFisZ/FgRK812P0V7ASo1tvetQUyUKqaKLtWca+ZoCM7NFhEIdmMLq9lDp0Nzw2PmhUqBsCBWAlvoY6Ww9Agz8S6TVdZ1OT9fxZEKO+yg0wFv6Ax+AlpZRKkmYwnQwhhjujZJqpgquCRqmMSkYLObYsuUMEmxLUklaxsdQMvYr7xd77NczZG7Q2R4umi4cf1QobXkir9F6sacmnY5M1OgG0zgWKvofot33n6Trzc23jMib7sTcnmrS70bYluCtckcchARpNAPEzK2xH4A1wQhBFNTU9RqNTY2Nrhy5QpXr17l7NmzTE5O3tdrfCdMaffHQ0lWSil+9Vd/le/7vu8b29pvbW3huu4hB8yZmRm2trbGx+xPVKPfj353t2M6nQ6+79NsNknT9MhjLl++fN/XMrK2/25KVlJK4jRlECuyroXSmm6YGj6IFvTDmM+/eIPdG2+wWpLMzc1x5syZQyoaWmveqPe5vN2jGyTYUjJXyfDkYplCxmLL79LRPZLAYrcX0QuNSrklBbW8S6Eo0LGPnc/SCRIzR9k/wLnLInS/CWtUTVnC8JxsKcwszQxsxrv60UzHHkonDeJhdach8SP8WJFzLbKuQ9aWJCqmHSRc3fF5bCGhlD36I+9HKW/U+3zlrTZvbPeP9W1SQ3HXas7wksJEESVG168XJISpImtZZB2bibzN69s93tnxmStlyLqSvW7Azb0ezX5CpPYtNvueYawEr24aGaS7hQDiVBPECRnbWIporekFIZc2euRci0EQ0QvBGxiC9FY3oB8mDCKFbQmKGYtawTXtQA03mgP6kSKWLmEa3tW+PgXS1GSiRAssrZBHHJ7oQ/Sr+w6lBeVshlMzBU5M5VmorLHT2CH85jUutwR5R1Ap5kAnhKlBU86WM/hRStaVQ51KqOQc3H5M049JU4xHlYCsbY2tVnb6IX6SHEpWBs14+ziljdzSzV6bKJCUrDwlz2F2bpaF+VmuX7/OSy+9RLVa5ezZsw88/97phXzlzR2afoTWZoPx5Td2GPS72FLzhY03WK7leHatytmh5cv9hhCChYUFZmfNdb744otUq1XOnDlDsXh3oua/F2jAT3ziE1y6dImvfvWrD+PlviNxp+r6+y0dcj9hWRZhrBmEKQXXYhCnNLsRgzjB1ilKp/Rch8WJCf7i46eYLBzd5rrRDPjz623coQ9SnGreaQzoRxGnFm20HVHvhsagUBso+s1mhGNbTJdcmoGRT1ouZ7i655O1Ja41WrhNpXO39H73hKVJ09uLg9YGvJDqFFtAMQuO7RJGKalSLE0W+MFTE9xo+vixIkgU7SAmiJWZ32lTDWx3Q0qeQ8WzcO2UdpCw3gp4o24W6omcw2LFo5J3SFLNy+s9XrjR4frQKfdu92MLiNMUgaQXJnT8hCg1BOWkF9O1U+wd6IU2vSDBjxK2W306foyfaJQWxnzw8KMYt9t6h/T2DocUhpNlCYlrSaI0pRskRCn0ohClM/ihgevdag6IEtP2TQyFClua6jHrWBQ9m6u7AwOwUJL2IL2HUvrhMOoV6kj33wfPVWZG5tkWJ6bz/PCZKRCGszU3O83P/miVf/ONN3l9s4OTBCxOV+lFRoR3Iu+wHqdIIYaux8PnJM38LFIaJxEoZUPGVE7SaJodQtVqzdBBYP/PNE0/5Z2tJh0/JiMcKlaR1Yk8Hz4xwdraGnPz8/zpK2/w2S98ncmpGk+cO8nqVOm+5M3ebvTZ6Znv+XYnZLPts92J6Pohi0WLfFFx6VaHZj/CjxRPr1Yf+OlalsWJEydYXFzk7bff5vnnn2d+fp5Tp04dKxl3PwCP72pS8Cc/+Uk+97nP8eUvf5nFxcXxz2dnZ4miiFardaCi2d7eZnZ2dnzMnai9EVpw/zF3Igi3t7cplUpks1ksy8KyrCOP2f8a97qW/XJLcG+Y6LcjpJRIbdj7t1oDNls+g1ijh9xdWzqUHZebXcWf3WjzF89PH/k6bzf6CAFTBTM8tqWmVFS81tqhUKmQdW2iRNMPU1zbGBEGtiJOUzZbAUkSEyvFn11vsduPcS0LKQVJou9bWmk/vHwUR0HSNZCzFa5j4zo2i5UcQkK7OyAjU5ZmCkwUXBKtubbjo7Wm6NrkHE1rAEGi6IcJjgXrQUKQd7AEpDrl9a0uOdcmYwuu7Q2o90IeWygTJ7DeighijSWlmY/cLYTZ8eccSZpq4lSPqztbCoSGRjemFyTckl16oSJURjdRaYEcGjAeuO9honoQVIprCeJUEwvFZjdACoPETFIFQhLECbE2NAOEJmW4wUhN6zaJFMHQ0n6pkqUfxTQ6KX6SYFvGu+owfufuun7Gm0q/JzNFM0U3CTjnSuqdiD++UseyjOr7cjVHKevw8adWKXzjZeKMQ7u1xep0FStbpB2YZ7/RCogTRZIq9voRg+HNCIb3rxT9ULPXj3BsyaPzRUqes+86JPs1nv0opRPE7AwUu9sDYmFAG0IIhAp5q6Go5ByeWCzz2rbPtaRMOpnh1e0Gf371T3n65Bwf//BZMseYrY6i3g1p+xFv1Hv4kWKnF9KPUvqRYrMHS4nptPix4o16j1PThbFP2YOG67o88sgjYxDGV77yFVZWVjhx4sQhy/rv9Jr4ridhWms++clP8gd/8Af88R//MWtrawd+/9RTT+E4Ds8999z4ZyNDsRF44dlnn+WVV145gL774he/SKlU4vz58+Nj9r/G6JjRa7iuy1NPPXXgGKUUzz333PiY+7mWkUXI6M34bmgFCiGQQrO5fouN3S79SBOmEAmziMRKU8oatv2LN9vER6jHpkrTCRI8R9IJErZ6Pte7TQYqQA0HuIPQyBLZ0syvtrshthRM5BxSrVmtemYuE6RGvDVNsaRECrO7Fwy5RxYcY15rrkVLtDJ9w8OQdLO4lTOSn/jAEj/26CyL1RyeI3GkpJa3mc1LMrbFZN6IkIapIucaXydbCmZKGaaLGfqx0dfbbJl22GY7BG1TzjpMFVxKnsNcyWMQat6uh3QDA2U2XkGC7nHSFbffGaYKDi0/oh/dXgClGM3vFH6UsNcLafkQa0GUmopGYyq/20u5JlVDjcMHrGT2AfXGPB9bgpDmOVWzWYquPX5ZpUyyGv2dHlahQZzyer1LvZcOuWrD9+vIx3Dva1RaDBPvg0eqBIkyfJ2MbWxdbjV9bjR9klTzdr3PCzdadPwES8B0XvCXv+9Rfvr7HmXOici0b1EQMRKIE1N5d6OEVClyjsB1jMqHJTSeY+Y+jX5I1pE8vVIZPheNUrcTldbwTqPPV9/e4xvXmryyq7i02cO1bvOKtFSkGZ+3djqst3xe3exSytqcna/y/Y+f4Ymza7x8c4c//OJXx+Cn46IzSPjGtSbX9wZsdwOafdOaj1NoBYpv3mpzbaeHHya0g5hu+N49fnK5HE888QQf+tCHaDabfOlLX+L69etjp/LRenhcG/D9hq3De6isPvGJT/DZz36Wf/Nv/g3FYnE8+ymXy2SzWcrlMr/wC7/Apz71KSYmJiiVSvzKr/wKzz77LB/+8IcB+LEf+zHOnz/Pf/6f/+f85m/+JltbW/x3/91/xyc+8Ymxidcv/dIv8du//dv82q/9Gn/9r/91/viP/5j/+//+v/n85z8/vpZPfepT/NzP/RxPP/00H/rQh/j0pz9Nv9/nr/21vza+pntdy2hmNSK2fSeTle/7bGxssL6+zl4Im74kkQ5aGR02sziZRNQKEhYnssSpZrcfHyIjWlLg2ZLnr7aIiOilAY4lKGUl2Yw0SSxV1Dsh9V5IMPyGGpV3TdlzWKu6tCLIOxaDoRZcIWPsN5I0JVFmvmVZ0iC/onS8I7/zI5ykQCoRh9oh5t8L1SwfXpsgTEwbZxArShmLQS9lux2xkneoFVyiRLFY8RBiJJwrKHgW13d9/CglY0uyriSIFU3fmCQWXHe0bUcjyToOrSCmmneQAoqeTaNrwAd3i6JrsTqZZxCZWdVodqUUhLHCHl6TZUmkbdMPjMOwlPrg89AMPafe3cIeDtt6ABlpdI1SrRHDtStMNba0cEVCf4jq0/pgbaQ19ANNogWxrdBKoYVAafWeTDmVFmiFoTDcj3CtHm5mMEm/6NpMFl06fmLazEpTzjmUszYbrYAbzQFrZctUk0CxWODChQvUGzv8iz95m7oPqbTxY40tzYanE8Y4UpBxLLQyaNiJnEPWkazVcgYdqMXYB2wU9W7A5a0uGcdipphh3Ya9RHOj6ZMbqtADKKFoxB2utzyiOKW0z7dsaqLMmnbIWuFYFuncuXNjQNoo9voRe35EP0wRWpB1JfVOSDJkgigN/SDhndC4RS/XcrgPMLO6V5TLZT70oQ/RaDTGmoNnzpyhXC4Dd/fSer/HJu86Wf3u7/4uAD/0Qz904Of//J//c37+538egP/pf/qfkFLyUz/1U4RhyMc+9jH+yT/5J+NjLcvic5/7HL/8y7/Ms88+Sz6f5+d+7uf4+3//74+PWVtb4/Of/zx/82/+Tf7n//l/ZnFxkf/1f/1fxxwrgL/yV/4KjUaD3/iN32Bra4snnniCL3zhCwdAF/e6lmLRWJkPBgMsy3ogT6uHEUopdnZ22NjYoNlsUqvVsKfWuHTzLeqpTRgH452uBNBmF98emDbObNHhqMmA1ppOGLM+aJPNQCFj48cpbzcCLiwUqHgObT/hRsunH6ZkhjjjwDdKFXGqqPfs8Qo3CBMjeJpqU5mNQADDbXqqBLYl8RwjObO/jaKVQWyBQiuBuKNVZEsIEk3Tj1isZHlsocRbjT6dICFINZOe5MJ8cYxiLGVt0IKcK2n7MdFwF52xJXnXwMoLGYP66kcJO/2YqbxJ5hoDlLCEYLroUsm6DKKUQsai0z5ICr4zLs4X6AQxkzkHP0oM2k8pBNLMrfRt4fHWIBm+K6bsksN7Vlqg3mX1MX6emMVLCgiGCDeTJI3BZjeIQWuCWHInI04zesvMwuzZRnIpUsZj68E2yke3BrUWJKkcuv8ef69q1AIdHuJYgmLWJowNutOVgt1ePHQSluQ9m0YvYqXoHVB4FwI2Q5v1OE+sI+JBRCo0gZbYUiIwG1FHChxHIIWgkLFYqGTJZxxUaswf77zUzVaA0hjzRaXxLJjMOzT7hpuWKVqgNV0/ZqmaZS/pEB9xu1IKqhMTfOTESa5du8YLL7zA5OQkZ8+eHXNTN9sBni1ZnvR4uz4wLgHDJzzEGtGPjDDyejtgtxthvyubn+NDCMH09DS1Wo319XVef/11XNdFSnnPhPRdObO6n7LP8zx+53d+h9/5nd859piVlRX+6I/+6K6v80M/9EO8+OKLdz3mk5/8JJ/85Cff9bWMEDvfbvj6yBdrc3MTy7KYn5/nkUceIVCSf/OtLW71YTPyCdPb+2+FQVcpIEo0riVZqWaZyB1Wa7je7rHhtzk969EcJPhxijX0s8pYFioVNDqmJ66BKFZEylQJBlmW8PJ6n84AEhGQpGbZi9PbHCtXjlS1NRYmWc0UXDpBzPbQKJD9yDfMl1trgRBGtUEDOceIjbYGMYuVLDMl40jbj1JaezDoRpSHbq0ZW7JYyfL6Vg8pbMpZmyvbfdp+QkaaVmOSGmRgJW8S9HorpOxmsC1BrBJ6Ycq52QKFjM2F+QIj140oVez2ekeq0BcceGqlwvNvNbi52ydMRpJTcrxujpII6cHtg9ICnWoQ8gGTwfEhMEnHjzUZNeTkSGNA6TkWKk2ILUhSMQQNDa9FMW7Djj5XloBqzlhfPFhVNa7TuHOl1wwTllRHWIcY0rXiYIJQShtEqjJ0i9iCRs9UN0sTuaGGoY3W5n5v/x28utkjTFLyXgaEJPJDtEoJEkUhY6O1EeZ1pIXnSKJU41iSgpvB29cy3R9+ogx6EIMEtCVMlD2aW33qHeMJN4hTShmb1VqeJFVcUU12fJta1iShaEirmK+YOfvJkydZXFzkrbfe4mtf+xpLS0ucPHmSMDEJ+cnFCh0/Za8fGaL6vk/SCCATDTeTz7+zy4+dnxlf48OKkWX93NwcV65codvt8s1vfpMzZ84ciXD8rq2s/n0Lz/NwHOfbAl9XStFoNNjY2KDVajE1NcWjjz5KtVodv+HXtrv8v2/scGVPEurbu6tRjP47VubL88RS+cCHNdWKjX6Xl+t7rHcCqlmbmWKGjC1whzvwQaKIUsVO14iV5l05VKUwjrb9WJEo2PNjImW06UYQgP3IdXNPwyRqmSQhUJTtlIZWpOqoj5nplWkpSNE4FsNZwpA/NQzbkpSzksSzGHQOrvBrk1mU1txqBVhSUsxYCCBBk7UElYxL1pHsdmOytk0161LvRYBpWy5VMqxOGLL0RN7lmdUq52YKfN+JKn90qc7rWx1afkKcmPstOrBStfnT166RYpHxPHQKJZnQD1ODptz3fA7JCyrQ2gahD1WV+2OoD3zPsIbnGYE7/ERjC00hb1MrZJjOQb0dUnIs9iLBIFJokRKEDF2Vx+8EUWLeg3LWph2EpPehzHOYtTD6yREJS0kseTtZ6pHW4hHr20iEN1FqPOPLOhZBrHhzu0et4HBupojW8YEFMkhSNlo+gOETSomwXXSUkKiEKB6K82pBok1nwJEWk7kcJ6fzxyL1qjmjEVjN3ZYUqhUyLE8o5krGkXqpmmOh4lHK2igFy5M5ru42afQDilaOONWcmsodkGHKZDI8+uijLC8vj72pnMklUuWyUM2yMpml68ekx6CYBrHizXqfbmiQmx85McFk4eHbFtm2zdzcHI1GA8/z+PrXv87CwgKnTp0aj2u+HfG9ZDWMkVvw+1lZ7a+ibNtmfn6eRx999EjZ/a++tcfr233CVGBZR9OZLGEqLCkFc+XbH5p+HLE+6PJGvctrmz32ekZ+J2NLJvMuy5NZuoOEomfh2hax0mSlQ6ISEmUqOD9RpGoIGtAHzzn65+jnji3JSskgTpAYW4m+H7BUzrJChnd2j2urDROWEGCZtuNSxWO+chR0Vhyq5m1LcnamwHI1SxCnrE9k6UaKnW5IzrHxHGGG0v2E09MF/uL5aZqDmDjR5DKSiazD/ha8JQUTeZeJvMsPna3h2JKuHzMIIlTsEyfGXv7M8hylfJabTZ+vv90kSIwahBRGkf5OBJ0GGLdAgeE857iEdb/7UynBtSSJNm22VGm0gqmcZM3r0w4l+WyWhq/J2JqMbdMZJGidHDqJwJCdzSJvkZDexZDTRMGz6AZ3fk8OX7357BrghC2NIkeqrWNv1Bl6eEnHRghNL0hpDiKyjtlknZrKs1jN0utEiH0vopQmiFMcKSm4hiSedSRJKhHKopAVlK2EgivIF7MkeFycL/PkcmWsfnJULFQ8NtsBm52QrKXxE6h3I85MF3lyuXyoDSclnJ8rUiu4NLohjk6Y8cpj37M7K6D93lSXXrtMZzvi2naFQSTJutaxXmAa6EcJk3lznj+9tsdHH5m+b1HrB4kkSXAch/Pnzx+Qb1pbW2N1dfW+WoTvNb6XrPZFPp+n2+2Sy+UeWrJK03RcRY1kny5cuEClUjn2zd3tR7y61SNRZrcrpSA84hOrMQvszaZB8M2XPbb9PnuhT2sQc3mrT861OTWVZ71t2hUbnZBEKSo5l+UJ46eUsQx5sj+AUKUorY0tvQDPMVDkRI2UI4AhUsuPU5IU8o7EESlxbMiSEslctcTZuSLWzgClNDea0THVgsl+aQKFnBl0H7WRFIJjW2dZ1xA2672I01M5PEtwddcnaJuZlOdIlieyZGx5CIBi7D0Ov/BSyebRcsrlfpucK8lkbfrK5tzS9BjevFzNcaPqs90NEZg5z34goRSmKjjYAh2dWAwpCOrAgvtAIUbnEcjh+RIUgzBm4eQsXiR4+VaHXhhjDYFDo/afjamCbXnb3VlraPkxlaxNNWtxo3W0TcooLMR9VIG3Cd0aiGMLJMeqXYARrO1Havj5N1B/x5JGjUXroVkl9MKEZN+z60eGm+fHKQpjEyKH/mxThQwfOTmBLRPanR6dVpcTNfjQ8gKFe8C+i57Nk0tlru302WoPEAIemSuxOpk7dl5kSTGEtcPrmz1uNAcUtwqUPJsL8yUemSse+v7XajX+ox/4PspXrvL//eo7+KnFqckyb2wbh+7DTxa6Qcz8cIO31Q7Y6UXMlY/mSb2X2M+xyufzPPnkkzSbzTGqeqQ5+H7G95LVMIQQY2JwqVR6z8mq3++zsbHB1tYWjuMwPz9/3+7CO72IJDVqAGkK0RGrtxz+DyHYbAe80egSCJ8gTdhoh3zzRos3632mChkmcjZLVY+9fkIwbO09vlBirpxhECb04wQpBBlH4vuCWJvlxRkiCUfwbMVooC8Ml0eba4jjBG1beBkLoSQ51yLv2uwNYmwp+IHTNV5Z73Bt16cfG/VrKYdk4iEYwbMtZoaWG1vtgJXJ3MH7lUOBubtEyXPQ2jgFL1dy2FJiSegECX6s6PiHFSy0BlID9tBoOp0O9XqddrvNRLnMx58+QSab5+rNDV7Z9scqBqPIDq0/kqFpk9S3F+80NZyr469agJJoeTthWUAlZ7E7uPfnL05B7UMuOjbkPYfEcrjUiAiihOYgRmBEh/OuQEhhzqXBkZKiZ+HH6Vg+y7EkuYyDJQRwfLKyhJEpureMkiAjIUgx1eUQvqk5vrJMUj0kOSuSoRWNZ1tkHMluL+SlW238OKXR6tBtK7IbHVYmcry20WYQm7/tB6ZKzDqSWiHD2dkiP3JumjBMCdU0GUvRqm9w6eVvMTc3x8LCwl3VGSo5hyeWK7S7DuWe4NzsvVUpukHCpfUusVJMFl0yMoLY4s9vtChlHRaPUGYXQlCdmuWJswI7bPHWzZ3he3FMKJgpuWONx6PoKw8jjiIEV6tVnnnmGer1Om+//Tbz8/Pvy7lH8b1ktS/uVLF40BhVUevr63S73fuqoo4KrWGu5OFYkiROx8aC+7/aGVugAM+GiJhvbtWZqc2w3gp4Zb1LL0ywhl/4G62AxYrHI7MFGr2QStYet9oavYhukFLM2DiWwJWCnX5MpM39G2WG23v/dDhESLRCCkkxIyjnM6QKyhmXuVIGhODUVA4pBTvdiDBVJFpQzjngC1AKx7HMbEsIvKFra8Fz6AQp1/b8Q8lKiMNtwDtjquDgWRaNTp9S1kFpM4tZqmaxpaDeDY+UW4qThN2dHRq7dZRKmZqaYmV55YC9SMGVuFLQD1Mq2dtlQcuPcWxJRkIYmzmILQSD8HY1cfc3W0Aq0ZbZIOQ8i6Ln3FeyAk06rG5GEP6MbbE6kaPpJ8SxopQx8G+B0T0UmESj9JCYrM180rZMtTxf9pguejR6wV3V1CtZi/mKRxAbsupx4UiQQiL0sN0L4zLZtEIP/40fKybyNoNYkSrTjr7R9NnoBLiWpNk39ILVkmQgBW/V+1zd6fFWYwAYC/uMKxHKbMCWJ7KcmymQtQ3iL28Jsp6kVjrF3Nwc165d48UXX2J5eYnp6Zm7SoPZkvuWN9od8qMWKga1GJHiuD5x4HCz6R+ZrEYhpGRxcYHUK+FtXiVIR0Yzt88tgVLOpu0neI4m51oHSM0PM45TXBdCMDMzQ61Ww7kH2fm9xveS1b7YTwx+EOh6r9cbV1Gu67KwsMBjjz32rt+8ybzD8kSWmUKG69HgkNOqJRjyaxR2FmzXKCckqeL67gDbEixUsvRCA2e2pGCnF1HJ2SRKH2gT+LFirxeRogxk2LNJNfQiiRBqrKptDdtwUoPrQMZxWaxmWapm6AeaCc+lnHOJkpRyzuGppTI3mj6XNrpoBWXPiIv2wnRoJpgSK8jYmiSVKBSNXkQl69AfmJ2+50iag5i2n9Dvh3RDdbwMlgZb2EwVjIneXi8h0QYBJoUwbc797q0a+oM+9e06e8098vk887MLTE5WEUd4NLm2ZK4gaSWK3X6E5xr7liTVZB0Di/YkQ4LxaEozPtWBkOL2kuPaBi4ugFxGsDbh0Tty8d9v+27am1II4uHfWtJUSkIIwiQlZ9tkcxbRkBeXJJqCZxMmCbEK0cqgOpNUo1OzGXGGYsAt3/ha3S1drk3kyXoOBTfEj45u8WoNWkkyrk0UJ/tmYEMQhgadmnbkgb/DADAERvXDzPwUEkmkU6JEsNePmM06ZG3BVNHly2/sEiYpK7UcO90IP0oJVIofp0bc1nL46lu7DCJDaF8oZzgzmyefz3P+/KM0m3tcv3adra0tVldXx7yiQ++C0kdwBI+OOB1KjA0/r0JDmCraukfLPx6YUCu4lD2bnV7EZCHL7ESe3lafWN9+R8z7BaWsy1vbPRYmsjyxWHnXShb3iu+08SJ8L1kdiAcBWKRpSr1eZ2Njg263y/T0NI899hjlcvk9v2m1gsv5uSKXt3q0egMGiWmjSG0SlW0JtJViuwnlnIdtQW04vO1HikLGVCozpQxbnZBUaQaRgW6frOXGySpJFe80ery9MxhybQyjP2PLsVdVRqakaPI2TOZtVqZKlLIOGjhdy3F+psw7OwMaPbNgLZWyrE3myGVsLGG4ViXPZsJzKWWNSeDNVoBrCzqDGDBKGJ4tKXo2lhS0/JQ0gTebfd7ZGRCnmjAM6bQUU40Bp6ZyB5+xFkP5Ik07MGTJ+YpLxrZQaHYHEb1Qcn6uiFKKvd096o06QRAwOTnJ+UfOk82ZXa5mKLp6xxxLIJgrWCxXi9zc8/ET85wfnSuQpoZ4LLUcwqEVGdsofQ8ifShZjbhRjmWI1FIrVAqDALa6EaXMUYvCaDpk8Ji5jIWF4aVZwiS9QsYYErYHmtmSxUTO5Y26UcgPY0XLj1AYhXU9LJsSNeLKCUCRpJpOEI+RjUeFaxkjzplShpvNAdlQ0L/D/0MrQEv0ke3C/WlcHkpYghEdQI/5RRIDY2f43LpBQssXVIaafn6ckrEEeccmU7HohQktP6beDtnrp/zp9RaTOYdyziFKFVe2+wyihKdXK0jLuEVUK1U2tza5cuUKpVKJlZVVstk7RaHVfVtgjDZKSZJiS4NC1FoziBNiO6AXRxScw2OBQsbmyeUKf3atSaMXknfMc0QfdDlwLPM5ymVsvv9kjZNT+UOv9bDiO624Dt9LVgdiv/J6GB6NYNtfRWUyGebn599TFXVUCCF4fLFkVNbbe0Q4dFOL5iBhz49IZUA2I6jkMri2YKma4/RU3qCobEGYKDK2ZK7skXdtGj1DNHx8sczJWhZ3SCi6vjfg6q6PYwmUNtVDlCiSNMEhJSc11bxDUvbwkgGPn5yiWjA8l+1OzHQhSy5jc2GhRJQY3tWIzQ/g2ILJgkuSaJp9M/+o5l0Wqh6J0rzdMMPqQsbMuPIZm91eRKQ03SDlrS2fUt4m51j4gSZsa95q9JnIO0zmXZNYlBi2+xRtP6bZN0rVV3f9oVyPUSLHSunv1fnWjSaO6zAzPcPE5MSRX0CVmgVWHwW8qGZZKHvESuNIwXY3ouOnqLqZx5WyxkHZD83iOqR8Hag8BCCtIbw9NRYwsTAlRLOXMjhQWe2Hgu+jJiQp0rbIOqa68hyj5pC1Ldp+wkLVw7WHKU5p+lFiHIAdibSGoJqsQCKIUkWQaHSqaSUxljTPcxQWty/BvF/GpDBKFJWsgx/GhGkyrIL0EFAiRnmVKEmOQbSN7kccSFhxapT3k1QzSJIxXYJhdR+nmn6YEKU2whLDzYHAtcz8LTOEue92Ivqh4trOgIwdcnIqTzXn0BokXNvtc2mzzc1myDMnyixUMrSDhNCtUFnK0282eOmll5ibm2VxcXHcAktThbgbOmRf1AoZZoou63sR+YxGSmNoOZF3mS17XO82WciXqWQOAyJOTuUpZ21u7Ax45WabhXLMZrMPEnK2xJYaqTStVpvHPzDFmZn319n8Xorr39VyS/8+xnEzqzRN2d7eZmNjg16vx/T0NI8//jilUul9K32lEHxgqczWWpaN0CF1C9xs97neSQmSDI4tKWVsViZzfOREhYJn3sqFkseVeg/HMpYRWceoOZybzXJuJj++3jhRXNv1EUJwYirPrb0BXT9EJykIQSXv8qOPTPN9pya4stXjG6+9TS9MiXVInMBsyTuArHPtw4u+Y1lmN+uZ+QNA3rXohqatKIQgGM4lbCnphwm2LZjMO+wNjJ171jLkT6MVZ9pCO72IyZwLShClmrd3+sbNtRtzaaND1rEoZ238KKXe9smIGNtJQFU4ffq0ITTe7W0bAlsOJKx9x0sphsRjmC16PL1UJec4XNsbMIgUUwUHKcSQsGxInv0oHQvIgqk8Im3kkqI0xbYEhYzEjxRppLC0JhWCoy7UkmYjECcGGKOFIAwtcnkjL6UxZO7dXkSUmgqwFxrJqZwrSVJNIWNzajpP04+ZLWZ4bavHZidEazF0n9bYwhBQU0xVP9rNTxVcLCl5p9HHj1MWKjm6YY9UKXRqHSBHp9pUf/deygQ6ASyFZQtsaVqSo79Lhy/oCPOagyilMEzUbT9hqZojSRVxqml0fa7tGHNQW4ph4hW8We+z249pDiJSpUlSzaWNNju9gLNzBYIkGZ/TkQXmZsv0+nVe/OaLLC0vMTM9A0P9yPsJV0ouzFUpugM2OgFozanpAisTWbOJAm712yQ6peYdropqhQy2FOQyDidqWZKgTzafHYONOn5CwRO8+toVpmlz+vTpQyarDyvSNL0rOOzb4VDxvWS1L0bQ9VGy6na74yoqm80yPz/PzMzMu6qilNastwI220a6ZbqYYanq3ZUTIYTgxKTHsrAJCnkeSRxK2RpCQicwTqclzz7wQVmr5QhTxWY7pDkkRi5UPM5O5w8clyhFlKSkcUAUBkyIhFzWRVsZFIK5ksfZ2RIZ2+bR+TK765JC3sF2PWqFDLPlzD35HJN5h7Ln0IsSavkMQkAvMF5ZJ2t5QJCoFD82/Jhqzh6SJ/PEw6rEzOuMmrjG4Kt1OpQq0nB5u8fVnQFFzyS1ONUInZITCQUVkHMhwGVpfppzp+dwjphHHf3wDezckvsS1v4VV2PaXFpzdqbAbNmjGyQEcUo5a/POzoBrez5+ZBQxDOHZSDwl6ajNZWaNpmIw1WRGguVY5KTNXhgfCeN3paToOaSpYq+f4AJr0w6VUo7dXsTisE3bDVIDtEgU1ZzLxFDw148VRc+mG5rfzZYz1Hsht1oD02pGDt1/BTZGWV9Kk6RzjsSxJJe3uiSpwo9T+lGKJSQOmlgcQRgftq/uCRkRAqHMObVWR1IVRt1GKQRhasAXJypZnlyq8MZ2h91uyq3dgFY/RgtwpEU/UkRKk5GS3X7ETClDJesQxoqpYoZ6N2S3H/P0SoW5okOsNVGiWe8mPL1yEi/1uXbtGltbW0xMTIz1CI+N4WejG6bcag6MgaIQzFWzrEzkDn1vtgY9YqWYyx3lJyWo5m02OwrPhrlKFj9O8aOUyUKGp09NcHoqi9a7fPWrXz1SMf1hxN3agKOq6nszq29jFAoFNjY2+D/+j/9jzCOYmZnhySefpFg8zIu431Ba8+LNDq9tdsdNncvbPdZqOZ5drd5VJiVUit24z1ytQh6zsxFSMFk4+m8c2+jnrU7m8OME1zJVxv5r932fre1tdrf2SAKBsD0W5yexLEk/SOiECadm8kwP2fCWgJorWZssUKwUj1QdOCo8x+LcbJ7Xt3rUeyFaa7KuzbmZPGuThk/1dsOYBJY9I4k0U3JZrHi0/IRrewPj/CsFIIljTVYJo9EGdMOEzXZINefguZJoJyYnTCswiR3WakWE46J6MVPFzP0nqn2RKrNIHzcjA0AY5YfyPqThbj+m4FoIrelp8KTR3htECQYgMYTtY5IrWCghwJLMlD3yjoSmT5CmJEqRasPjsgQUPYtS1mYQKhYqLotFCyfuEXQiFioVzs1XaA0iHOkTxAm+0BQ9o+5hWxIr0bi2wI80tiVpBzFhpNAKEkwCjWPDb7ItiWUJ8q5lqjgNO/3YeH4pTTXr0OonDEJTvWhuNy4FZqZiCVBSHKvEsD8yljTtrU7A3d4uKTQ7/YSyo5gvZ5iveFQyLt+82eKLrwVESpNzhqLUStELUoJhReRIA7Ypesbtea8X0fJj+lHKVickSCLsoaL6VjvgyeUqlUqFra0trt+4jiUt/IE/nnPuD6GNieggSvnmjRaNXkghY5NqzaWNDt0g4bGFEtYdc6/dYECiUhbzB2feRc/m3EyRa40u0RCa7kiJdgRL1QzZjM3CRJHHlxZpt9tcvnyZL3/5y5w6dYrFxcWHZjH/vTbgd1G88MIL/Nt/+2954YUXWF1dZW1tjZ/+6Z9+KDuUejfi8laXiZxDfiglFKWKdxoDFsoep44YjCqtqff7bEfRWKZ/FFqZVoQ6xn5VCIPqK3r2vr9R7O3t0djZod/rUa1W+eC5ZV7fiWn0Ivb8hCTVhIliecLjicUSjm3kldASISyUNppKwro3JDtMUm7u+Wy2Q+LUoAFnSxkzRxs+gzPTpi+/1Q4IU83qZJb5sjdUspbMlTw22gauHEcJ7YHgfCVLbZhEzQ4zQcYh9Y023V5KznEpz1QNctByyVjGOXb5Dij8g4RSIJHD+xf35eF1opZjseLx6mbPCKdagjAxySFjKYTSpNrYhyTaNgK4qcZOFbWcQz5jBIYnbRfPMecW0khlFVybUsZlruJyYb5CKWsTRQnPvXyN3VaDHTeiNlnj4kIJ15a8st5BIIxdRpiYtmyQUhmCDa41fFzHCMTGsSJM1XD3b6oqBzOrsqSpjONU40cCtKA3SLEsafQW75CbMsnR3HucmgR9SPDijghSk9g8aROHx2s+dcOU680QCQz+dJ2feHye2XKW1za7hKkatv80YXpbtT3EWF6utwJmSh6VnIMQkA51JG/u+ViWmX21/ZidfkCiNKemChSzNnPzc2g0m5ubfOvlbzFRm2Fqdo5C1myExD5rlI2Wz04vZKHsjdGDUaK41fKZr2SZKR5GA+4FPreaAzyRJWNZzJY8JvIuH1ydYLvZo7HTIk41rgXTBZfposd0MTOmeYwU0+v1+pise/bsWWq12nuueu7HePH9ju/qZPU7v/M7/KN/9I/Y2tri8ccf57d+67f40Ic+9FDP8Ud/9Ef8vb/393jjjTd4/PHHefLJJ/n93/993nzzzYdWSpvZgSbrWmPvmbxrkbElG63gULLyk4T1bocoNTYZyZ1OfQwTljhaHGF/BEFAo9FgZ2cH27KYmp7m1KlT2LYR9czlA67u9Gl0I5SGuXKGxxYM4k8oxqq5UgrUaJVO756wklRxab3LrXZAIWNjCWgOjKDt7D7YvByy/I9i3NuW5LHFElMFl0YnJrYlThEuzpaQ0khX1Te3qW81KWcdahNVqjNZ3t7x6YcJk3mL+bJLqqCac8ZV4rsNlQqI7y9RaaWxhOY/uVCjHya82fCNQCmKgmXs1puRzZmpAmGieGenT5iYVmGt5OE4Fv04IevYWJYZytuWZqGa5ZmVKufnS8aGfl9kHYuTS7Pg5oiDNlevXmVqaooTtRydIDbozuGMjKHS/JOLZV5Z77A3iIlTTda2sITA0RKJqbAcS1LKWZyazrHVDnh5o2u0HLGwJIQJRCol51oMdHIgGQkMuCOfdXAsiR/GxH56z3bgyIE60gYPeNQ6Gymo91NQkk7QQWvBD5+rsd4OSFLFbZbC7TdsNGrqBjGpUgRJwlQxwyBITLsXTc6x2e4G9ALjLnBrz+ffvbnDh1arzJQyCCHxsnncqRrfeGud/pUG87UJLq7OM1HIsNuP8aOUd3Z6WFIcgLm7tkQrk/DvTFZxqri03uFWy0diUbHylD2XDyxXODNT4KNnq0S7NxC1SfphwkQ+w5npPOfniwfg6iPe09TUFDdu3ODll1+mVCpx7ty5e9rW3y2O41ntP+9/sG3Af/kv/yWf+tSn+MxnPsMzzzzDpz/9aT72sY9x5coVpqePdsR9N5HJZPilX/olfuZnfoZ//a//Nf/0n/5TbNt+uBYhwsyYXrplCLhCQMmz8ZyD+mhaa3Z8n53BYKyyLC0LdQwyUWuQ6nDC0krRarWo1+t0ez2qlQonT5ygeAcgRAjBUjXLXClDlJjdtDNsSUo1VHcYo8DkwVI/NXOMo1wudvsRW92QmWIGZ/hlLXi20VdrB5yevj/kUkZKVio5VioQhiEvN6HV3KNRr9ML+kxMTHDh5CKNgcLJmirKcwTXdkNcyxB4J/IOZ6YLh5Qn7ju0qapQAq0FUkuUOHrzoNG3FSUEzJQ8/urjFT73ss/Ndsx00WNxeopeBG82+kSpYrKQIYgVG+2ActbmkdkCnmOx2Q4I0pQT1Tzn5mzSZKgqYlkHEJf7Y7GSZbsTEmemyOZDbm03CJTF40tTPLJYY7cfEiWaUtZUud0g5erugLmyR3NgqphBlOBIU4XZ0ijon53OUys6bLVDiq7xiEpTQJoWW5IaV8ecYzY0CjPrs4cySZWsw2zZw5LwynrHoO7uAo1XGjp+aqSUtDAKHxL2c820Bp2a708vVrx4s0UvTNjthhznnWkLKOcdukNFk1t7xqBzrpQh41jsDSJa/YhuaDh+M8UsriXoBQlXtrpM5F0GUcKbzQQdRczPz5MEPjc2dnhzs01tokohl8O2BDf3fMIkRSlNxrHIDSXBlNZHCuautwKuNwdMF80s2BYJSWzx0s0W08UM5YzksWmXH/zBE4SxMQv1nOP1+KSUrK6usrCwcN+29XeL71VWd4l//I//Mb/4i784NlD8zGc+w+c//3n+t//tf+PXf/3XH9p5fvRHf5Qf/dEfBQ5C1x+mkK1rCTbaAQKzo0VDoxsSKc2zJ6oAhEnCRq+Hn5hd8Aix5Mf6UBtwf4yIukpAFIY0Gg0aOztIIczO+sQJnHtIPNmWHLPypR6qg99xjJQCre9sRxoFgjtnWIMoRWvGiQpMzss6FnuD+5Dz1hqJ0SQEk6hG5p7r6xvMzExzavIMtiuZSxRXtnvUuxE7UUQnSDlVy7NQ9UwrKDXAltly5q5ipUeHQOrb1hphomn2YgZxjBJmnlDImCQ+ulaDJEzZ3d2l0WggheRj56fwrQLb/YQkVZyYdjk3W+StnQG7vRDHFpSyNtPFDH6s8IfISdeShHFC3xfYwix4t/YClqpZqvnD7+lkweXxxTLv7PTpBIK5hUWssIfVXqfvhZxeWjoADgpjs0HJ2JKViRwzpQw39ny2OyGubTFX8QCN41gMIk0545B1bASaKDFeZWq0gZGSjA2lDOwG5vNTyEgjAaQUc2WP1ckcqYI3t3tsd8JjhXJHBf3oeaLEUJ5pmKhScft3w/Bj8z737uKa61iQsSwsz7hsG4i8mRFKjEv2IDZu2FnHwrNtpNDU8i71XshX39rlxmaXa3sR81MRRdelUixTOF3ka5c3eWN9j8dm+kzNzTAouPzptSZ7g5iZoodjQ862mSl7TOYPfw6Nj5U1Bl8kWiFsn07PMqoz4ja/K+Pcf9JwHIdz586Nld2/8pWvjMVnH6Rz9L1kdUxEUcQLL7zA3/k7f2f8MyklH/3oR3n++efft/OOkpWUkjRNj1dLeMDw45Sy5xClmr1BMhSElWSH+nh7vs92v49Gs9uLeG2rR9uPjfBnEFASMSfUbbvx/aE1tPZaNHYatLptyuUya6urlB6UnKw1UstjB6VGBPWI3x2RsGw5XMA5CLyOlcJz7t63NMlSoLSm3W5RrzfodNqUSkZR4NFHH8UaPQgt8Byjc9gLE97ZHZAqWJnwDtz7ZjscWjzcf7KSQ2V0jaYfpbyxG3FlMySs30JiWoulvGS56nFmuoAQ4A986o06zWaTcqnM2tqakdoaPoXTY1sKc/3n5oq0/ZgbewNu7gVU8854tvPO7oBGN2SvK8lIB18ntP0Y2xL0/ZTqMfzPmVKGWsHFj1IsS5B1ZgiCBa5fu87L33qZxcVFpmemEcLIX00VMmy0A2p5xkK/lhScrOU4N1vEcySDKMVB8mYuw+WtAeWchcShG8S0A1NN2tK4C+ccieW4pEpjW8aWpJhxeGyxRNYxRodbnYBuGNEJ7wfQbpB/qTY8MPONOfy51hgppHHuHCJJ9YHXkkb9xbYQQ25WxjaUiXzGNhqcGiZyDgq42RywPJEnSjSvb/RwnQFxENGJINdPeSvtcXrGtNZcL8ts1kPYEW++fY09naXkOvQTRTeIEVLQkwkXFksUj5BESpVG3vF91UAz6dMOA4rOe0sWuVxuDBq7fPkyN2/e5PTp0ywsLNzXOnGvNiD8B4oG3NnZIU3TA06/ADMzM1y+fPl9O+9+uSUwvlMPYzfRDVJWJrJkXYvWwCShkmfTCWKut9tYQ1JgECte3ezRCxOmixksIdhKAq7vJmx1AqMxNowoitnZ2aFRr6PRTNWmWF1ZwfYefDYzShB3Y8MIIY+v8O5IWJN5h+JILibvjiHrIJg9YrC8/zqiIGZnd5d6vY7Wyuj0raxgWZIXX3yJA8uP1ohUoC0jJeQ5pkq480vjWAI/ur9KWTAUnx3eapRqLq13eWcvZNdXFGxQGJJtOZvhnYYPkQ+DPaIwYmpqiscee4ysdxgpZglxQJS0mLEpZmw8W9IaJHiOxUTOfN4ubXSIIs2JiQyFoaKFH6fs9IzludTHA2wsKca8OzBebWfPnaXZbHL9+nXqjTqrq6sUi0XOz5nFdqcXEqcaz5U8tljk9FTBVNsayq5EIzg9U2C6kGGrE5DNmIRrS0GKJElSQmUQgWtTLtW8SxinbHZCnliu0AtT3moM2BuENLoRccqYx3X39wNcG6JYkA7bfhz4Shok5eipjmZckttzVZ2OVB80sdZYQtLxYxBmJtfxEzxXkrEkfqrZ7oRU8kbZfbvj8069SzOIWShn8KRxCOgMfab2+jFlz6btR2gEjp0lytjs7nQI4xBl2SjPJiOlsTg5Rmh2ppTh1Y0O5aw95nENohTXkvjCZ8ePHgqyr1qt8uEPf5itrS2uXLnC9evXOXfuHJOTk8f+jdb6e5XVd1vsbwPCwyt9y1mbKFXMZ72xm283Cnmn1WPeuj303O1HtAND0hztsgoZGwvNRitgvuzR6XRoNOq0Wi2KxRLLKyuUy+XxB1wcMcM6NrQetrnufehRbcADsS9h5TI25+cKXNnqs90NAMi6Nmenc0eioNCafqdPvd6gOdTpW1paolKpjO9r1JY9qvITQyHYnGNAI0rdJm5qrYkSRfEIAdtDr4NAKA48j51eyHY3wLMgVYpK1gIEu72QeuIT+QOSrsUPPDJPrVbDkg/+eZkouJyo5Xh7Z0BrECO1Joohn7Fxx/dhhHJtKUwVo4bivuIoB96jo1qtUiqV2Nrc4vXXX2dycpLl5WWeWinT9g3IIudY40QnhjYmWoAfJQyilO87McE3rjbpxQk9FVOxU6RKcPMuqcgwSDSJUvSCGD9RnJzKMV1wubHnj9tfJc8eq+En98hWElDJUHR3dJ9K7xPzGD1vjY2imLHpBEYxwxUCKSDWhuCcdSzCMCXWsdGlHP7pIE7ohlDK2kwVXBJtPLRSpYn6seHGJZpbeyEWiqIn6QUJKSZp9cOE1iChmLWwpWA31LQTG9vSFGRMNumSy5ZphSm3WgFPHXGfi9UsO72IzXZgDCKVMhuEqTyVrMNWZ49UP5w5uhCCubk5pqenuX79Oi+++CLVapWzZ88e6QA82qTei2f1fsd3ZbKq1WpYlsX29vaBn29vbzM7O/u+nXekYAHmDX1Yc6ulapY3GwPW2wHVnEMzGLDZG1DO2kwVb1dCI4UbeQAEYQRlt3aavNK5SZqm1Go1Lly4cOSg9DjQxZ0hNONZwP2EqazucbS6DbqYLnpUss4YBVj07DFkfXx4mrK3s0t9q0EQhtRqNc6ff/SQHtvwCsb3dzg0MjVw3lrBZasTjrllbT+mPAQUHBt6X9tv37qfKkXXj9Bak8l4aNVld3cXS0p6gwinkGV5dobJSp6Z6SpHtafuJySCM7MFJvIuzW6M0hqtJTsdM9cc9M2cL+talHMeOdcePwuBRB2DmDsqLMtiYXGBWq3G9RvX+da3vmVag9PTt3fuWiO0RGszk3q70efGno8fpSilKFgJ7XYPN9FUSy4T5SortQJKaV7b6mILYcSU8x4X5ovUezHlnNHJ60cpWdfGdQRhnBAmh+ej41vRpl1uCYEnFUkysnQXpiW4b+10LSPgmyamXa5Txq3I6VKGp5bLnJ8t8ZW3d3lts0fOVcSJxsKoZaRK0Q8TTkzmmS5nuHSrQy9KyNqSIFGkQ61MPzXIvXwuJRpoWoMIIY1liNJ6KJUl8JOUas7hxGwFFYe02i16saRXsoeozINvWNaxeGKpzFbbY6dnAELTQ5UY4zig6KmEW50OC++B83nnZ+HEiRMsLi7y1ltvHesAPAKbfQ8NeES4rstTTz3Fc889x0/8xE8AJrs/99xzfPKTn3zfzjuCdg4Gg4cKsihnHT6yVuXPbuzydrNJqjXTBZfT0wVy+1BqBdd8MY2bqCDwA5p7e/SChOn8gIW1BarV6j3lXvRw8T2yTTQCL6T6gdZWKY+fZx14+dTo3ilhJJhmSod3Y4HvU6/X2Wvs4bouU9PTTB6j07f//Obyj74GDWSkxWPzJa7uGdUAjWax4rE6maeQOfqjLkaL33DAppRRTxglZtcaJukkREpBnChSEpyMR22yipI2U/kMQkn0Xazq7xUWgpm8x3TeJOqca/OSapN1LEb2hWGqKWZsqvsG9FqDpQWpvP+EBZDxMpw5c4ZWq8X1a9ep101rsFwsDVvCJm41fS5v9chIhQi6tFtdEiWZKhfIZj2mSh6xTllv+sTK2L67jmQinyFjG4mjejdktuSRao0fpqjhNNOxLFwrPWQsqjEt4bmCS8axmCtnmcg7VHIuz73eoOUbWahUAVKhMETcGIuYlDgxlVQlb1PJeZQ9i4sLFT6wXMGyJLv9hCBOSJVZV/qRxrUhVUZqaiQtFcdG9qrdN0r6o0Z5HIEfx8YsdDJHrGF1MmfEcwcx9W5ItedgSUmkNI7rkSnZlP0+7Z06b72lWVtdwrlDxDbrWKzVcqzVDnMCVaKQwqYVBsQqZblUPkQsfrfhui7nz59neXmZN954g6985SucOHFi2H436+C3IxndK74rkxXApz71KX7u536Op59+mg996EN8+tOfpt/vj9GB70eMSuCHbW2vtEbLmNUZh6lKeWgHYXNnzqnkXGaLLq/f2iUJeqAU2s5QcC0+8vjZAwoJ9wo9HNiqfQuoGO+YHyxRwX20AccnGSWsg8lyDKdv1Ol3e1TLE5w+fZp8vnBfi+xYb+4e11BwbB6bKzIYctc8Wx57r6NqCkySUiq9PaCXgiAICFp1OjtNUstlfqJET0niJCXq9Vjf3ObcYo3ZUs1UOUq8q4Ql9RC8su86FyoenSDmVjMgHi7mRc+0V7070GBmzTYQ7wfKWEClUqH0WInNjU3efP0K5coEK8vLOK5LmiqurO/S2m1hJQOKhSIry/MIy+VmM8CS0PUT3mj06MYxUayMDFDR5UQtz2Q+QyeI+NatNlvtgLlKlihVDIaIPSGFAQ0d+JpphJLMFlxOTOWxLYuLiyXyw03dh9Yq/Om1Fp4tsVREKiw2Bgm2MNJjSWqR9xQ9PyYJIxZrDpPVIv3QtPVqBZeia5OmKXPlDEGcstOLCWOj/h8pxV4/oh1ExLE2FdWw3N7/ziotCEMzsyp4xnqnkLEpZGwm8y79wCiPeLbRAFys5lCVHAtFmzTZ5cUXX2JxcZG5udl7CuNKLUhjNZZ56scxV9stVsplnHfRdj4uCoUCH/jAB9jd3R2Tis+cOUOhUMCyrLsmq/+gtQH/yl/5KzQaDX7jN36Dra0tnnjiCb7whS8cAl08zHBdl0wmM55bPSyuVZimtMIQOYQ7HxX9Xp96o0G8s8uskyHIVchm8xQd8Bs3HihRjUJrjVQmYe1Ht727OAYNePSh6FQjLQjjiHqjTqOxgwRmpmc5uXIKx3nw+zGeffdR3SlB1raOVE03l2dmU2l6kBslhPlfu92mXm8wGPSp1Wp89Kmz3Ogk7PUixCAiTixWazPMZzVpe5tbVwesrq6SzeaM67B1/09ZKmOieWeSsS3JhfkSC+Xs0EhTMJFzyLpHPzcNZiPCg29ELCFZnFtkamKK6zdu8NJLL1GpVOj0B9zcTqhWSpTLU9xqRbx2rY+mhxAwX/Z4ZaNDJzDK6Ik26hf1TsBX397lh89M0QlSPMcyArFaG3h+lNKP07HEVtY2lVaaahxpkfMszs8XafsJNc8htw9BWvQcso5lVEyihM2+xsUm4wxnm6Pdh5RkPBehEno7m2wmVQZLJWaKHmtTWf70akB7EOPagjRVaKFZrGSp5DNkHUkSaZS6rUV4VKQKbuz6nFsostMNqRWN8KwA8p6FI23myhlcKenH5jmcmaswWZim3W6P9QZXV1epVquHFnyhR/JNDPlZt59DkCS802qyWqqQecg6gJOTkzz77LNsbGxw5coVbNu+J7jj25GshP52Tcf+/yC01tRqNf7gD/6AJElYWVl5aATkQRxzo9Mxkj3DSJOU3b09Go0GQRBQm5ykNjVFPm/4KFpr0jjilUuv8PTTT7/LmwKpNeo+laKPi5s3b6FUysrKyr1PqTFAkHqdVqdJqVJmemqaSqnynq7hhRdeuMtM64iQHEpYYjjvUOp2q08I05cfcaMsyx67n4769IlSdPyEVGtKno1rG8PFNE25desW9bqZpy4sLCAteVsc75gQQ1uMdznmusvrAlLft36j1EPwAoIwCNje3ma7XgetGSjJhp6gGULLT2gHEa5loTUEccpEwWGrHTHKJX6sSIQi1cYo8bGl0hCnp4hTyGaMdYcjzeI7V/ZodI1Yb2cQm+erjJV93jOSW44lOTNTYH6ocnJlu8fNvQEL1Sw7O7u0E4tubCSdWqFRinEt0z2YHsp7ZUhx4g4XahZnTp5A2Vn+1TfXebsxwJKQdeSwc2AEnLdaAa9vdrGAXqKPBSA5EopZmx87N8PCZIbdgbGncYYSX4WMzc2hvuVUMcPKRI6Jffw4rTX1ep0bN26Qy+VYXV0lnzcdATFE6I7inXfewbZtlpeXD1yDLSVLpRL5I3yxHkakacqrr77KxsYGMzMznDlzZnyNoxihpu+myv4w4ru2svpOxUh5vVAoPFRicM5xWC6VuN5u0x8MaNTr7Ozu4mUyZmYzMYG1T5nAUIkEKh0OutX9WxOMQmgBCjRiCLp49/sSKcU9kVujBb9eb5AkCbVajYvLj5HLZO6tuH1fcW9r+wMxFKFVwgwhhDLXqPXtKmow8KnXt2m1WpTLFU6ePEWpXBpzo0ZhS3lgoRmFZVmsrKwwNVXj6tVr7Oy+PHSardAMQ8LEOAmXc44xPcTMmNSdJLSHFHp438fQkW4fp8HSpjrodjpsb2/TbDapVqucO3uWdmLxJ29scmt7ly1f0k0s8p6F5wi00swUM3TDhDBJqZY9/DCh5Nn0w4QAU7FutHySROPYkvKQWjD0SkQjKHs2tpDMl3NjzcGtTsA7O32mCh6nZ3JcWu/y9bd3KWZsSllnjIJs9o082FTeIe4P7Wdsm5xrzCSlMOaQGVvSHKR89NxJ5hyfK1euUC6X+YnHFri05bPTi5BC4NmCUsZhKp/h315ukHEs8rYkGUQEd4BAhDDYDs8x8kk7/ZCffHKWZpgQpSn5jEWcaN7Z6Q+vxdAW7mzf7reEv3XrFq+88oqhaiwuY9sHP2sqTZFHuD0kSnG93WaxWKKUORpEFCWK9ZZP24+N43XZo5q7v8RiWRbT09N0Oh0cx+FrX/saS0tLnDx58n1PTnfG95LVvhBCjOHr5XL5oSarNE1p7+ywd/MmV5t7VCcmOXf2LLl8/q5jhlHpr5UyyIX7iNHQff+6blCC4l0nrLvxrPr9gQFM7O2SzeaYn5+jUqkaF1wlUGNppvdWxN8vyGN/pIlp8ajkdhWltabZbFGvbxPHCdPTU6ysrB5AQD1o5HJ5zj96nka9zmtX3qaRZhHZCtIxquVzlQyPzhTJWNaRFvAPN8RQv/HoCktoULFia2eH7e1toigae7RlPI8oSXn7nSbFYpGPTJb4t5c2aLdj2n1jgVLNOiCG9ibawLclgoxrKqFOP0FbEMSGBO37MVGqyHs2tXyGth/jx8Y7SmiBHya4lsCPU3b7ERnb4kQtZyxTbEnZc9jrR2x1AkqezWI1a0SXU42OFWXPYbtrBJNdBLYw3mASsykoZx3myx6z5QoiW+b1qze59OeXWJ2f5tHTc4Akb9nkPZtBlDKRb5F1JOEw0SqtDko4afN5tqWkVnQJopQo0UzlMkgJe0HIS7faBElKxXNItElcgyjlqZXKIYuQ0YZnZnqGG1dv8MILLw7nWXPj9pvSGnkMAElpzY1Om/lCkYk7/KwGUcrX3t7lZnNg3ALQlDI2H1qbYPU+xZ1HXlYXLlxgZWWFK1eu8OUvf5mTJ0+ysrLy0MQT7hXfS1Z3RD6ff6iSS/1+n42NDTY3N3Fdl+WFBS5cuMDGPv2/u8VIYiZVCot7JyuhTRV11Cu/l4QlR5a3w0hTRbO5R73ewPcHTE5Ocu7cI+Tz5gsgh+220V/o/VXOuwzzfbi/vx+h+lBG+cCyLfwoYGdnh52dHTzPY25+nsmJCeRDGlILBFPT01zv2zSvbWH3N5itTZLNF7mx4xP6iqXJHK4lqObcscTV+xLiaDmsyI/Y2tyi0Wjguu54Z79/IWz7CZ2h2KoQUKuWqAcd4jhBpglZx8GPUgZxQq3g0A8VgTKGjanW2LakkJGUMw4FT9KPDCy80Y0MatOSnJrIo1PJVNHlncaA7U7AIErYGSRM5Bx2+xHdIEFKQTdMjHahgCiJiRPF8mQOV2oSDSvVLOfniry62UVrOFnLUatk0BiDRSmNNuWb9R5v1vukVhlVyvLCjT3eWd/lB86vkp+eojmIuLbTp+0nuFKCpQhTMfYe2//JsyxBreBS9hyyGWv8XioFm82QQZgwX72dOLKORaMbstOLjhRuFho8N8uZs2fpdDpcu3aN7e1tVlZWmJyYMJXVPeZGG70usUqZyd/mSl3Z6nJ9d8DSRHacJLfaAd+80WS6mDmARj4u9vNNi8UiTz/9NI1GYwzCGClhvN/xvWR1R+xXsXi3yUopRaPRYH19nXa7zfT0NBcvXjTSO8MdiOM4XG+375mwjJfSsLK6W+gRd0qj77LLebcJa8SzCsOQen2o4m7bTE9PUaudGX+YtTYwbD2cgxw493tMWIZvcvzfqiF0WinD7LWEAC3o9npG1LffZaI2ySPnHiFfyB9q9d1vRElqFt0jBGV7QcKen3B6aRadhGxtb7O326JjF7na8NnohLi2ZDLvcGG+fCzg5uHEcC4mFZ1ul+2N262+06dPHxI23vdn+/5T4A3nc5ZtE6cp9aaPtEDaLt93coJBnPKtm13CROG5kpojWaxmsYRgcTLLRjsgzNrGhDPnMlf0yLs2Wx0jIrs5FPGdKWUodkNsW7LeMgKDQZIYfzKVkmrDB+5HCXEKZ8qacskdX/N8xWOzFbDdC8l7NsWsTS+JOT2dJ041bzcG5DMW+YyN0B7z5QLXt5t8643rXF3foimrJMJmruKx24vY6oTYlhgDPKJUkSjIOZDPuGihaXRDHl8sH/Cka/YSsvbBlp0ljYTYfiUVP07Z7UWoFAqORTXvIoSgVCrx2MWL1BsNrl69yubmJkqp+1KwaAwGxEqxUCiiNFzbG1Aeqt6PYrqY4UbTyHmt3Ed1dZQ4wtTU1Lh9ef36debn5+/5Ou81vpes7oh8Pk+v18O27QdOVr7vs7GxwcbGBrZtMz8/z4ULF47s7eYch5Vy+b4SlhCGtHhsDGHT5uB7X+eDJiytIQh8er0er7zyCpVKhZMnTw4NKfdd512quvFrKQ5B6u8/jkYk3smNkghUqqjv7lJv1AGYmZ7h1OlTuK5zpFL8/cRgaP1QH9qp1Aoua7Uc5X1ab3GqSZSxg7CcHGtLK1y+0eDmdpNcNsPkQpGMa9PoRby+2eWDq5X3rYWihoK625tbhFHI1L5W392i4tmUsjZ7/YhaIYNrSzKORbMfgZAIKVBJSlYFlGXAf/LUKhcXelze6DKIFbv9CEsYh+qZnEvHT4iVYjrvsVjOkXUsukFC1rUIE7OpuLhgtCxzGZtbTZ9EpfSCmCDRtzlRw/abUtAYhNgKlu2EYl5xuuQxV/Ko5V2u7g54u9Hn7EyR89MFTswUuLE3IEwVtYxrNinKbDbKxSKTxUnazV3eurHOcq1ErlzlsYUS5dyAK1t9amWPqaIh667vdpGWTZgqMqlgIu8cmmXmMxZ7/RChnTHAZyR0PEpq9W7IqxttuoN0TH5eqmY5P1/ElhKEYHp6msnJSdbX11lfv0W9XqdSqdxzVtQKAhKlmM8XxyLM+8O0wu9fEOA4XUAhBEtLS8zNzX1bpJi+l6zuiP2SS+Ex1hz7QynF7u4u6+vrNJtNarUajz766JFQ1DvjfhOWZcljKysDSX/whf9+ElYcJ0bFvdEY764effRxXPeOQe99VnUHzn0Xbbvj4s6Z1X5u1AgwEQ5C6tt1ms09CsUiqysrw4p2NPsbcsAeEMIfJSnfWm9T74aUPAdHws09n3YQ8/RyhfwQUp7LWGQdSXeQUPEcY7BoZZmsSkTss3njBrWZGpP5Art941B7v8Pu+77WMGS7Xqe+tUXGcZmZnjPIRkfSjRKu7Qzwk5S8YzFVdA/B4R3b4sx0gVc3u6y3fFp+TBAnQ5kkiZSQc12SJKXZ7vH6q5dYXVnhwtMLtAYxlza6NLqB0be0JBNZl/Wmj5ezhnp6EUGiODdTGC7etwmnc6UMShmJrN0kYhAadXdLCmwEidJkLEmUpjQGMBVrzpa8se3GbNkYFt5q+jwyZxyzpRxB+4doUHV7TyeE+T8rX2F6xuXtxh7d9ZsUCjmqpTzzFY8zMwXKWQc0ZOIuOuORaMnZmSITeYd+mBAnamyvM1/22GgF7HVjKjmbBJPAqzmX2tAS5rWNLn6gmS15SCEIYsXV3T6lrHNglmRZFsvLy+zt7gLw4osvsrCwwPz8/F0rrV4UcVO1mSlleH2rRyXnjFUzmoOYYsZi8gjA0FFxL9m5bxdZ+HvJ6o4YSS7dqw0YhuG4igKYn5/nkUceeeAh/f0krCMrq+GCb9bud/dhGSeNfdwcraHf77G9XafValIoFFhaWkJrxfZ2/ehE9QBV3fjP3kWFJYTZHKSpGoM9xtyoVpv6Vh3f95mqTXHhwgXDezrq3EMO2IMAHeq9iJ1uxNxwcQHIORab7ZDNdsCpKTMnyNoWa5Ucr2322E0jpIT2IMa2Lc7MzZIhot7Ypt1uQa5K8i42Gkfek9b0ej22trZo7u1RqVQ4c/LMgVbfbjfi5c0OzSAxVvMKqgWbxxbKZjHeF3Nlj7xrUe+GxjbDHpBzLCpZG43xm9LCYmJ2hqmy4rU33qZaKnBibZUPr1W4tNGj3g2GXD/JB+YrZDMWoVLkXMnZmQJL1Sy7gwhLms2Aa1tY0rQQE2Wco//sWotukKARWFLgSmNGalkCB00xY+HeoeRvW4KMY8xNwdznhOtiI/CDdOxtFqeaOFXMlDK0tmI2OjGFcplqKaXZbrGxNSCQHq2BO/SOArSZP81W8qzVsnSCBClgP693qpjh4kKRt+p9tjtG+WSykOGRuQKeI9lshrT7CXOl2xqgniNxpeTteo+FsjdOfOP3F83S0hJSigPzrNrk5LFEcD9J8LKaybzDtZ0BnmORKOOn9dTS/begkyS567r27VK3+F6yuiNG0PWjkpXWmr29PdbX19nd3WViYoKzZ88yMTHxnhSR75Ww7qysRtXUw1jmRnOkKInZ22vSaNQJw+iQTl+z2To0L3q3Vd343A9QYY1afGmaoJRCCFP57e7usLu9g2XbzM7MjnUl73nuFCyL+4bUj2YNB3UbBa4taPuGPC4xoJK1Wg7Xltxs+gzClKmSiy0NqVcIl3wux/WtHZqNbZoVxcTqEta7JHaq1HD1tra2CMOQqVqNxy8+jpc52OpTSnNlu0fPT1kseWhpFsCtTsgb232eXjlsKVPKOpSyDuutgErWoZCxCWNDDqsVHHpBwmYrwJY5/NwCG3st3tl+mYtrszyxOE/HzxGEKRnHYmKoDZhojbTEmIYxmXNZrGa5vmsWU0sKemHKbCnDE0tlXNui/uIGsdKkSo+raEsKbGEW4m6QGMHnoZt1vRdiSQONN+8LTHouJyp53moOaAex4chpQwSeK3lc3RkQJoqK5eA5DjPuDFvNNkHbRwaKJGsRJintCOZyDkvVLKmGbpBwbnbYutsXi9Uc00VvCBIx6jTS0qAMCRn2iS0rTb0XcWNvQJKatt3yRI7VWm78ummqkFJQLJa4eOEijZ2GIRVvbrK6ukrhGBfgjCNYmbZYqmboBpqca7FYzY55a/cTd6ustNb/YQvZfiejVCqxvb19IFlFUTSuopRSzM3Ncfr0abLZwzYQ7zbulrBGldVBSPrD2cn4vj/kfO3gZF1mZmaZmJi47Rk1jANySw+hqhvFvSqs/VVUoVDgxo2b1Go+YRjSbrWYKFc5deo0xVLxgQETtyH19z7WseRQYPYgTDceOuQam5UhPB7BYiXLQsUjUcaj7OX1DvVeRM6xCBKFly/zkeUaaW+Lb33rW6ysrDAxOXnfO9Rxq297G8dxDKpvcgrHso9cPAyiLjGw81E1LI0vV3NgbEcKx+y0PUcanpNn4wytM1KlafkJu72IuXKWUtbFsWu0+zmubDRp7uyysrTCwsTBdrgjBALjfYUwSev8XJFS1majZaSlTk/nWKrmKHo2f+FcjbfrPV661UFpbSoQS6CFwEqNhmbetbjVMnb2252QJFXMVzwub/c4N1Wk4FoIAedmS0wWXLYHEUoZl+bZUgbbkuQci5lShvYg5oYfA5pKLsvZ5SKLXgCDDS5OTHDZT8m5Njv9ECnE2FTyqHBtyWTBtNokAmKDzCx4NhnLYhCl5FyLei/i6m6fQZiyPJFDA69udohTxSNzJcDIjI1Rq0IwNTXNxMQkGxvrvPraa0xOTLC8snLkPMt1JNLVnJ0rUXQfnJ7x3WAPAt9LVodiBLAQwmjDXbp0iUajQaVS4dSpUwbm+5AEJO+M4xKWlKaysh5AJf1uofbZ3vd7PaoTE5w5c5ZCIY8+lkxqdq23icYPL+6ssO4ETIihwGw2m0XKFtvb22Rch0fOPkKpWHpv51b3l7BqBfe2R1fBRQAtPyYjBbP5HEdJFgoEjhTMljwsKbnZHND2E6o5wxVaqHhIUaXe3B36TDWGsk1Hb4JGrb7t7W32dncpl8ucOnWKUrmMHNubHP3OjH48zhtDKS60HlJ4j4/5ssdU0SVKFP1IDcU5DNl1vmLU9WGIjtQ5HPLMlFKuXr1KvVFnZWXlwD1prQ0IBlMmOZZkbTLP6nCh3l+9Zhyb/8/T8zQHMfV+NDRjBFcodKr4sxt9Vmsmobb8hGLGZqGaJ+darO/4BH7KB1erZGyJJWG25DFbzqLlwXsuZW2i1MDvi549noE1/YSPnFpkvrDM1atXsSqaQiGlOjlBPmMsRe5OQdgnHG3+SdVzWZrI8vZOn26QcH13gB+lTBUzzFc8cq6pMG+1AlYmzb2kqTokXGtZFktLy0xPz3DjhrH6mJ+fY35+4VByUVrTDIJ3laySJLnnzOp7bcDvQAgheOWVV/iRH/kR/qv/6r/iL/2lv8QzzzxDLnd/BLr3GocSlgZbWKgofc8J4pDt/fQ0J0+ePGB1LjUHZlijEFIgUvVgg54HCK0ArUm4U0w2ZGenwc7OLrlcjuXlZaqlCjdv3uLK5cssLNyfGOi9zn2vhFXI2FxcKHF5y6ABtVaUMg6npvNMHGFTfmdMFVymCq6RIhpWF5hbZmaiRqVc5tb6OpdeeYW5+Xnm5+bG3Cet1LjV5/s+01NTXHzssXECkIpD9iZ3RtGzKGVtWn7MVMEsWEoruoOUiaIzNng88tqLGU5O5dloBYYIjKnUJjQHOENCQ962aPsJxeoE01OT3Lp1i0uvvMLs7KxZRO3bFAephxX1cKET4nBtHKUpQaI5M1vkRBzT6/fZavn4qQA3Q6I1bT+m5UOSas7OFJnKu6DAKxl4fKMbsVjd1/bSGpEylOMyP8q5Rgoq1cYXTQgz01LazLVyuQKPPPIInW/8CXKwxyDuMrO2im0d304TDMWN79xAKDg/a6rJtxt9lNYsVXPjRAVmHrodhPhRSs6RaK3GnMs7I5PJcPr0GXrdLlevXWV7u87qygq1Wg2Eob5M5/JM5Y6xl75HpGl6T5fgb0e8LyXCtWvX+IVf+AXW1tbIZrOcPHmS//6//++JoujAcS+//DI/8AM/gOd5LC0t8Zu/+ZuHXuv3f//3OXfuHJ7ncfHiRf7oj/7owO+11vzGb/wGc3NzZLNZPvrRj/Lmm28eOGZvb4+f/dmfpVQqUalU+IVf+AV6vd6B1/g//8//k5mZGX7t136N69ev8+ijj3Lx4kVOnz79bUtUoxglLAuJ0GZhe5C+sNaavV7EG9s9Xt3ocOXWDpevvMnLr7zCwPdZW13l4mOPMTc3dyBRmb81i8j+zCi0wEGSpg+znjKhlEKlKXEckyQpUpkFq9vt8tZbb3H58utorTl//jwXHn2U6YkpbMthbXWNc488wu7uDpcuXaLb676n69DKyA/drWacKmT48FqVD69VeHZlkmdXJ1isPFgr2BLyULtSKXAth9WVFR45f55Wq8XLr7zCzs4Ot27d4sUXX2T91i1qtRofePJJVkbVlwaZMrY3uet5peTMdB7Xlmy0Axq9iI1WgGdLztQKpk11THiOxeMLZc7NFsZzrHMzRVYns4xGllKZijuMTWvOsSxs22Z1dZVHH71At9vj5Ze/xe7O7vizrEd/d0zs9EL+5J0mf/ZWg3c2drhyq06SppRKRYrFAqV8hmreZbroMohMVdRohaSxeSDWkKMYxEdPJoVifN9RovFsSZRobrV81lsBiTL6ha3hTHJ03RcvXmRiYoLXXnudN95440jUsByqiBz3tZVasFLN830nJnl0vkit6B4g6AaJwrEkrm34WcA9LUEKxSIXL1xkdWWF6zdu8MqlV/B7PVbLlXedqODf8zbg5cuXUUrxT//pP+XUqVNcunSJX/zFX6Tf7/M//o//I2CETn/sx36Mj370o3zmM5/hlVde4a//9b9OpVLhb/yNvwHA17/+df6z/+w/4x/8g3/Axz/+cT772c/yEz/xE3zzm9/kwoULAPzmb/4m/8v/8r/wv//v/ztra2v8vb/39/jYxz7Ga6+9NjYn/Nmf/Vk2Nzf54he/SBzH/LW/9tf4G3/jb/DZz34WgH/yT/4Jv/Irv8Lp06f5+Z//eT772c/ypS99idOnT/MjP/Ij78cjumfkHIelUombzTaWvAfP6o64ujvg8laXVqdHv9dDKcXqdIlnzz1KqXDvxVVrxm2aEWgAHlzq6G6hlLqj1SdI04RGY4+dnTpKwOzcLKdOncZxHDMTSg+mkmKhyIULF9jc3OLy669Tm5piaXHpXe8C1QHS8tGLaEZKprLvXpbpuBgBXQr5PCsrK1y/fp2333oLx3FYWl6mVqsdaLUYqsCDtWOnihk+uFJhuxPSC1MKnsVsyaPo2UY4Fc1xyLKCZ3NxoUyUmIXftS0ubXR4u95HpgYh58eKbhhzZsag3kaRy+d45Pwj7O4O2531bdPuzJm2n6lyDtIeBmHCN65ssrXbJCtTTtUKbAd5Gj0DWIhThedYVDyHjG2RsSRhqAjihDhJhzNWk2Ay9l0W+dQAPnb7IU0/YbroslDJolAMQsVOL2R5Ijd8j8x30LbtsWHljevXeemll1iYn2d+YQEpxX0Dj3Sq8WyLpWqOSxsdbCnGM829fsTaZJ5ixh67Pxwnt3QghKA2NcXE5CTN7W1233yLN9sdzp49+65n7MfxrA6e9v1vA37bVNf/0T/6R/zu7/4u77zzDgC/+7u/y9/9u3+Xra2t8VDw13/91/nDP/xDLl++DBibkH6/z+c+97nx63z4wx/miSee4DOf+Qxaa+bn5/lbf+tv8V//1/81YOwdZmZm+L3f+z1+5md+htdff53z58/zZ3/2Z2Pl8i984Qv8pb/0l7h16xbz8/N8+tOf5u///b/P1tYWX/7yl/nFX/xFPv7xj/MHf/AHvPbaa99R07FBFPOlb76E4zgsLC7e8/it3Tb/7vUN/EGfat6jXC7j5XI0ejEX5oucqN3fDksMqwyDoTDzu1dfvcRTT71L9fdhGLVzdQCoMAJ57DWblEolZmdmqExUzPyMEXjh7q8bBAFXr13FH/jGcmGi+q4VKsSRLUF9wP/qYYfWit3dPba3t+iHg7G4cX34XBYXF5mdmUEIsQ/c8nBDMHSYvs/HlsaK1za7bLeNYG/GFhQ9m3LOBgQVz6FWdA+oJ6TJbZX66ekZFhcXbws4WxDFMY16nVevb/F2G07MVamUy0hp0fZjXrjeYs+PybuGJ1TNmY3MVtN4UE3kXZ5YLCKEmWFVsg7PrE0cSJ5Hxf/7xg4v3GpS8oxGIJgqcbMd8B9fmOGJpQpRFPHCC3/Osx9+9kBS73Y7XL16jSSKWV1ZY7I68UC4oxTNlXqXW62AIE5xbMlc0ePsbBHPkYRhyDe/+cKh8x4X+9t+QRDwxhtvsL1tNghra2sPvJl77rnn+OAHP0ipdHg+PEIDep73749TcLvdZmJiYvzv559/nh/8wR88gF752Mc+xj/8h/9wLAnz/PPP86lPferA63zsYx/jD//wDwG4evUqW1tbfPSjHx3/vlwu88wzz/D888/zMz/zMzz//PNUKpUDFhsf/ehHkVLyjW98g5/8yZ/km9/85vhaRnJLP/qjP8pv//Zvs7e3x+Tk5Pv0VO4dOddhoVRgexAce4xKU/aaTer1Ojf3fKI0z9m1JTL7hqlZR7HVCe8rWY0IviCQwgjQjkAOWmv82MyVsq51yJ77yOsbyh+lY26U+ZtWq0V9e5sgDJmamuKxixfxRrs/DVZqRmT3sy57nse5c+fY3dnl6tWrNIZghXcjTmsQisOFGzPH0/r4ls57iTiOqNcbbG9vI6VkdnaWs1M1LNcCISiWSkwNvY926g1OrK5RKBwNU36vYdpyGPDB3d5XbRK3kJLHFsp0JxOiRLHdCbjRDKh3DRACYcAZjy2Uxrwhy7ZYWV1henqKa9eu8a1vfYul5SUK+TybW1vs7O2QLxaYnVvAz2sm9rVZy1mHs7MFru/6VLIWnSAhitSw4jYtu6mCSydQSKGo5R3OzhQMevD4opFR02K5kqMZROz2YnOtEqp5dwwgUUqZDdAdL1Qslnj84kXqmw2uvv0OW7lN1tbW7nt8YCF4dLbEykQOf9hGLWbs8XmUSs1M9j6+a46ULO6zDPE8j8cee4x2u83rr7/OrVu3xlp+95tc7gaw+HY6TH1bktVbb73Fb/3Wb41bgABbW1usra0dOG5krLi1tUW1WmVra+uQ2eLMzAxbW1vj4/b/3XHH3OlJZds2ExMTB44ZXctIwWL0mpubm9/RZAUmYU1pheQgviEIAur1Ojs7O7iuy/TUFLnpPNFm70CiGse9Plf69sLMPgCAVAIhJH4CL91qs9tPUFpTzTmcqOWOZcLf2eqTUhBFMTs7OzQaDTIZA5U/CmEph22u/UnjXiEQ1Go1ypUyN2/c5OVXXjYVyezsA1dZ5r4NsES9D34e/X6fra0t9vZ2KRZLrJ1YM0obw/MIdbvKKZXLPH7hIuvrm7z+2uvUajUWl5YOzRsfRmiAIwRwRzGqcg+0Yz2bbhCz3grIWIJa3rTf49RYU0zmXVbvsGrP5nKcO3eOW7duce3qVZTSVCoVLjzyKLlSnkYv5Ea/OSYLw+2F8dxcnjjRBKGi0Y0Q2kDwz84WWKhk8RxJ3rUMaESbxR4hsKR15HovJZQ8m16QMDNdpBMlaDS2FMSppjCU0zoa5KCxtEQpmJ6ZZrJmQCUvv/wy09PTLC8tY9+H0ahWUHAc8u5hpXyl9CEqyVFRcF0Wi6VDnC+4vYnf2toaC9CeO3fuQAFxVIy6IHerxr4rFSx+/dd/nX/4D//hXY95/fXXOXfu3Pjf6+vr/MW/+Bf5T//T/5Rf/MVffHdX+W2MQqGA7/vjL8bDtAl5t2FZFhkpWayaGdZes0WjXqfT7VIdQuqNTp+g48dkbJ9eaIiSAOmwGjo5dfxOT2gQSqOPWJS1hjSB6x0o7flU8y6WkDS6Id0g4enlMqV9u887qygpBd1uj0ajYSrsapWzZ89QLBQP7RYNgorbq+EwgT6Inp9jO5w4cYJarcbVq1fZ2dnhxNqJQ6ZxdwvzPIBUPzQYktaKvb0m29vb9IcuxMcpbYySpRLDuSGShYUFapM1rl27xsvfepnl5SVqU1Pvw2IhDicsPVyUj0FztAYxfqwOkE0dS5KxLTY7wYFkpVLFzs4OW1tbxHHMzMwsqUrZaTSoNzIsui6TWZeFssf1PZ+ca2FLSTdIKHkOTy2V0KmgOR3TDxPq3ZB+lNDsx+z1Y4qexSOzpfFnUmuNVpqU1HwehTyUtJarORq9kK6fUM45xFrR9mOWqtkx2nNEzL0dRp1D7asu9tt9XLt2jW+++E2Wl5aZmZ255/uktR5XpPs3A0ql93QGmM7nmb4HiEIIwdzcHNPT01y7do0XXniBqakpzpw5c2wVOFr/7gWw+K6Drv+tv/W3+Pmf//m7HnPixInxf29sbPDDP/zDfOQjH+Gf/bN/duC42dlZtre3D/xs9O/Z2dm7HrP/96Ofzc3NHTjmiSeeGB9Tr9cPvEaSJOzt7R15nuKQCX7z5k2A73hVBYZnFccxjY0N1m/cYCeIqdVqrK6tHSIBlrIOJ2tZ3qgP6IaBUQ1QmrmSdzRrfch50UOTxuNitxfTCwWn8g7u0ETOK2ZYbwdsdUIKGesQYGKkm1iv11FKMT09zdoR1zwK67jB9JA4fCc35l5RKpW4ePEi6xvrvPbaq7dnJPf44pnncftcUt1/dXdUxElMo95ge3sLISQzs8Zx9Z5D62ErdD/3LeNlOHP2DK1mk2vXr9No7LC6ukou/z4gVoeQfo2BYN9NT1GPABp33oO43T6No4it7W3q23Ucx2FubpbJyZpxVsZ8D69fv863hon4wmyNkmdzqx2QpJqVCY+1iTzljEkelZzDrabP1d0BlaxL1rHQaPb6Ma9tdihnJ8i6lllIpblIpTRa6mHCEuOkNVV0eWKxzLUdo/doS8GZ6QInpwrjVvd+Yq4cKtof94n0sh7nHjlHq9kyShPbxr6+Uqnc9ZHrMWH79isfTpK3w5GShWKJwgMYIVqWxcmTJ1lYWODNN9/kq1/9KisrK5w8efLQZ/J+ktV3ZWU1NTXF1NTUfR27vr7OD//wD/PUU0/xz//5Pz/U5nn22Wf5u3/37xLH8bid8cUvfpGzZ89SrVbHxzz33HP86q/+6vjvvvjFL/Lss88CsLa2xuzsLM8999w4OXU6Hb7xjW/wy/+/9s47vK3y7P+fI8nblodsDS9JjuN4BCcQCgQIUPZoS9/SllJaMhiFskOBpPAWKIUCCYS93lJGKaOhhTJKgR8jrEBCyI7tDEvylGRb3kOydM7vD1mKHcu2ZMsj4Xyui4sr0rH0aJ3vue/nvr/3FVcEH6OtrY1NmzaxYMECAD766CNEUeToo48etpaAWH344Yfk5uYG/z0dSJJEe3u7f7xFZyc+n4/ykhLiU9Q0tHeO2PJUkJlEakIMTV39eH0iaYkx6FLihowx8D8BYW/Wu31+KTvwKxunFGjt7sOXEReMovr6+mhqaqalpZmkJL+3YEZG+oi9UAIMjPEeZSGSFBSNSARLoVCQl5tHpkaDxWJl23b/JN/0tPSQ61BIw53dg1FOhILV09OD3W6npaXZb6prMpGWHk7hx+BiDgF8EoJqf0O4IAikZ2SQmppGfX0dO3fuQKfTk5OTM2TadDQQfP7PZqzXnpoYQ3yMcmhEL4r0enzkpCjZt3efP+WpVg80Mg8fT5KQkMCcOXOCQux0NmEyGzHN0iCJEjGCYth3tbG9D5VCQcLABZSA3wm9sb2P5m4PebH+PS8hYCI5sPnoE30IiqGpwcxk/yh6UYS4GL/TvCTsFw1R9O/dKkN8R0YiLT2NeWnzsNvt7N69G7VajclkClYqh0KSJPAR9K8c4l4xiKSYGHLVamLGOY8t0A6Un59PZWUln376KUVFRUP2swL7VdNZZBZgUqoB6+vrOemkkzAajTz//PNDVDkQzbS3tzNnzhxOP/10br75Znbs2MGyZctYs2bNkNL1E088kXvuuYdzzjmHV155hbvvvntI6fq9997LPffcM6R0fdu2bUNK18866ywcDgdPPvlksHT9yCOPDJauD17LjTfeyIIFC1AqlfzmN7/h+uuvHzOvG228Xi92u536+nrcbjcpKSn4fL4hRSLdHg91rR3j7tHdbw8U3pew1tXL21/tZH6RkZgYFaLgL7Zo7HRToEmkRJ9MR3s7DqeTnoEUl06nH3OTOVAaH/ZPIYI9rAORkGhyNlFTU0NqWiomo5GYmIAdDv5S8FF+DQIgKUcXS0kSaW1tw263093dRWZmJnq9fkRT3VDPIYRah8CQJtbB9Pb0YLFYcbv7MBoHKiEnenKRGFKFKShHT8VKksTepm72OnvwDXg3dnb3ENPfhT6mj2xdFnqdjoQwiw5En0h9Qz32xkYyMzPJy8tDFWKP7ou9Lno83mHO9Q3tfZTnqIftlQ1erzQgPggCdW1ubC099HlF4lQK8tMTyNckolIKAz6K0Nbais1iY/68+WG9hgPp7++npqaGpqYmsrOz/RcXY6XXlALO5ibsjY3MPeyw4O1ZiYlDhixOFEmScDgcVFVVoVKpKC4uRqPR0N7ezqZNm0Zs4RFFEaVSOSUj7idFrJ577jmWLl0a8r7BT7dt2zauvPJKNm7cSGZmJldffTU333zzkOPXrl3LrbfeitVqZfbs2dx3332cffbZQx7vtttu4+mnn6atrY3jjz+exx9/nKKiouAxLpeLq666irfeeguFQsF5553Hww8/THJycsi19Pf3c8kll3D++edjMpnCjiYnSldXF/X19djtdhITE8nJyUGn0wUHOQYiwwDjEqyBSq5IP/Vej5e167aQkqEjS52AQoA2j79qypjYj6fT5a9m0+nIzMoKK8Xlnys0jq/fBAQL/BV4VpuN9rZ28nJz0Wv1YYdrA/Mch4lGMNXnHEhl63RkZWkjKhPe39M2yvOPIBqSJNHc3EyNrYbk5GSMJuOoV++jPgf+iOrA70g4gmVv72Vv3YDjiArm5GvJMejGVwwigafXjdVipau7i5z8HLS6oXs/ux1dVDR2kp0WH4xY3V6R9j4vR5vSgt58I60XScLS3M1OezfxMUq/k4VXpNcjUmpIZrY2ecDaX6Kl2UVdXR3l5eWRv5ZBdHd3Y7FY6Ovrw2g0kpWZNeo1o7PZibO5ibKyMlQKBbkRpv0iwefz+Xv89u0jMzMTrVbL3r17OfHEE0Mef9CL1cGMJEkUFBTwyCOPkJKSgsFgGLIfFm0CU4Xr6uro7OxEq9WSm5s7pKehaWBi6FFHHTXs7yMRrEijqeAafT58osjXm3fQoUiBuGTcHg+iu4tkoRuzLg2dTkdaamp4fSAMNIJOhAkKFkB7WxvWfRZiYmIpKDCHHf346+r9abmenh4cDjvNzc0kJyej1+uHzM8KlyFFJaMeCCiE4FC/A/F6vdTW1NDc3Ex2dg7Z2YYRbXpCEYymRnJeUAj4QpgOu/vcOBwOnE1O4uLiMBgMaDIyInruwQQFc+Dfba2t2Gw2FDEKjGZzMD3f1edlc107rm4PSbEqfKKE2yti0iRyWE7KmBFmv1fki30u+n0iaYkqBPzDJTv6vCDBcYUZJKlUSKJEk6uZRruduYfNHddrGoIEzS3N2Gw2YmNjMZvMJKeEjpTsdjtt7a0cMa98Qmm/SHC73ezZs4f6+npUKhUnnHBCyAuOgBXTVIjV9Bs+zTAEQQia2aalpU1aNWBfXx/19fXBqcI5OTmUl5eH/EIoFIqg8/iBJMXGkpuuHl2wBhVRhCtUkigiHlAwUVZoxGK10tXdRrKgID8ni9yc2cTGx43qSzfoUf0j76Pxlo5zHymAQoK0lDTKy+f5/et27MCgNwy4EIzxoBK0NrtodNrpGkj1lZXNHZct14hpv1Gem8A8rhDvuUqlwlxQQGaWv4+pudlfgJGaljr6OqTQ+3UHIooSSsA38BZ1dnYOzNBqJT09jTlFRSSnjC0SoxGqPD4tPR21OpVG+/7y/bz8PJLjY5ifm0pdWy/ODg9JsQLZafH+SCuMNfR5RXr7xYFxIv7JApIICSqB1m4v7j6RxET/SqSBqcZRQYDMzEwyMjKor69n566daDI05Bvzh534RVEkPS4ec4h91skiLi6OuXP93+nq6mo+++wzCgsLyc3NHfb7mJEFFt8Vwh3AGCkHzsPSaDSUlpaSkZEx6gc+1jpGEyxBkiKy5ZFEcWAcydDeqCank5aWFuLj4khJjqG9o4O4WBUxMTEELvJHEyz/lNboWjYFvfHG2Ecasg4CxRz+fysUCvIH7Iyqq6tpbmmhoKAgZLe+1+ulqcmJw+5P9WXpdMyePTvkXko4KBhuIRUukm9g4vEIEVZKSgpzy8pwOJ3s2buHtLQ0jPn5xIS4Ag70tIlhfjY+n0hrcysNTjs9vT1os7TMmzePuPiJ2VAFBXOEdSiU/vL9rMxMrLU2tm7dSm5uLjqtlhJ9CsU6KeITZ8B/z+0ViVWpBr7DEm6PiApQKQg2FEuSiCAJ+x3jo4BCoSAvLw+tVovN5ndOz83NJTs7G0EQUCkU6BLi/QuZBmJiYlCr1RiNxmB/VklJSbBKeqoc10EWq5CMNoBxPPT399PY2Eh9fT0+n4/s7GyKiorC3lMYLbIKrvlAwQpEUz7GTM1JA+J0YG9UR0cnTU4nnV2dZKT7B00mJycjCAJdXV1UW6pxuVooMBf4UxhC6BPv/o36yck4CyL+5x7jN3NgamkwiYmJzC0rw+5wsLuqivSMDIz5+ahiYujt9Vf1NTf7qxvzjUbS0/en+gQiN6MPx0JqLKRRIiwAYcARIyM9A1uNja3b/E3SukH7Pkox/Mq2oFg7HICA3qAns3jOuAdHDlnrQF9bOCIQGxfHnMIiXB1t2Gw2mpxOTCYTKSEuMMYiPkZBdlo8e+zdKBUCCTEKPB6J9m4P5swkElRC0EHCX0KuCPoJRkuwwB/JFBUV0dHR4R+t4nRSUljIYWYjltYWvNNkJOvz+YLz0rKysoKCmp6eTnFxcVRn+o2FLFYhCLhYTFSsOjo6BnzQnKjVagoKCsjKyop4HpZSqRxTrGC/YNW3dfrTKBKjClWoVJ/o89HsctHkdCIhodXqmFU4i9iYoeqzuIcAAHgHSURBVFfkycnJzJ07l4aGRnZV7EKn05OXl4ugUuwvsR7op5XEaPs/HPhC9j/+SIIVVhQjCP6Te0YGFouFLVu2EBsXh9vdh0bjn5wcqrFYGlRmPBYCAvjEUXvaIiH43KM8XGxcLLNnz6a9zW/b1NTkt21KSUoOS6j6+nqx2x00NzeRmJhEfr6RjIx0/6tRBJ25xk3QpDiCx5CAdHUqaeXlNDQ2UllVRXp6+ojR42gUZibh80k0trnp7O4nRqXAlJnMHH3yQL+ghCD4/KIV+O1OgmCBvzdwXvk83O2tuGwWtra5iIuLm5I9oVAMdlxXKBSYzeZgf9YXX3xBbm5usDJ7spHFKgSD04D9/f0R/a3P58PhcFBfX09PTw96vZ4jjzxySOVhpCgUCnw+37AptaFIio0lJzWFelfHiD+jwam+wb1RTmeTvxcmOSUYPShGKRRQCApyc3LIyEinutrCtq3bKCgoICVdzUA2ZVL89EK/KECSEJRDB1T694TCH7Hi9XpxtbTQ29uLoFDgcbtJSkom22DY71sY6ul9/mq5UdpmB/XnRFe6pcDE47F6odJSOeyww2hsaGDXjl1os7LIHdGlXqKjo5PGxsagr2dxccmw73Fg0rPfTzDShQ+y9xrXW+IfOJmTnU1mZia2Ghtbtm4lNyfHb7EV5kVhjEpBeXYqprR+3F7Rb8g7xJvP30ricDjR6bQD4iUg+KRBLv3RQaVQkJ2aQopBS/+sAvbu3YvNZiM1NXVIT+pUEcpxPTY2lrKyMvLz82lqapLTgNNJwMxWqVTS1zeygexgenp6qK+vp7Gxkbi4OHIGfjDRGFoWuLIJlImORVJcLDkZaupdHcHK8FCpPkEQaG9vw+lw0tvbG7T/SQy7Ks5PYkIiZaWlOBwOKqsq0WoyyTXmo1JO7ddLGCgiEQb6YgKl4OH4XvT29uCwO2hubiYxKSnYyOzzidTV1bF9x/b91XUjCXhgH+mA5/Pv1wnjqtIPF0kEpSDgG+3EKfkba3MNuWSmD9g2bRuwbcrMJFBg0NLSQmNjIx5PP1pt1qiuI/6HlfxFIhE4tgcqUyccYQ7kYONi45g9ezYd7R0D0aO/sESdOkZqcCD9KA1MCB5sAdDX20tjYyPNzc3BZuZAz6NC4ffLFCRQKsd438MkMTaG3FQ1MQO/8ZiYGEpKSuju7qanpyfYtJubmztlAjHaLKvk5GSSkpJksZpOUlJSaGlpQaVSjZoGDNgJ1dXV0dbWhlarpby8nNTU1Kh+gIG0YbhiBfsFq7a5HZ/oG2Im29/vDZrJxsTEoNNq/b1RE8iLC4EUWmoa1fssbN+8DWOBacobqgPFE353nTFOIJJEW5u/gbezq5OMDA0lpaVDUn0qlQKTyeR3wLBaaGlpocBsJnkEZxPJJw2ZOqwYGJw5FRGmGHjuEFoqDNj4BATT71I/B5erFZvNisPhJCkpEZerFZVKhV4f2mB4JIa4fIzx1Q+k/cJpcwibgbScOlXNYYfNxe5wULW7aqCwxEhs3HCxFYJCNfSFBCLKjo52NJoB/8bBlZ4DYzEkyTfwO1dOWLA0SYnokkOf+P3j6/NISkqisrIyWOQwFb8tr9c75oXKVCGLVQiSk5OpqalBqVQGB58Nxu1209DQQENDAwA5OTmUlZVNWl55cGQVDgGn5BgB9OpEGto6USgEuru6cTY10dbWRnq63wA3VT3c9mY8CBLgg7hY/6iO5uZmLHv20ZLRgslkmtL0hcKH/+x5QEowgNfrDRqpiqKITuffl4uJGfnzS07ZP+ixorKCrMwscvNCp9AC0Z3AGBZSk0BAqEVBCopBqMGVfgQSEuJRq1NpaWmhq6uLjIx0CgpmjWsybECwpBGcNiae9hsFwf9e+8VagcFgIFOjoaamlq3btpKTnYPBsD81GBiQGHhPJNFvMtxob6Svrw+9TkdBgTn0/legAi7gNSh5ESUFSoVi5Nc+AkpBQU5aCimjjLIJ9DJptVoyMzOHmNBOZKhiOMyUkfYgi1VIkpKShhVYSANX4fX19TQ1NZGenk5RUdGwCa6TQSBlN1axR2CwoTgo1ZcYF0NMfx/b9lrx9Pej02oxGo3Ej2PO00gEJ6MK+9eblZVFamoqNpt/ZpHRaJz092rwHC7w7ykISiFY+NDX24vd4aC5qYmExERyc3PRaDLCbuAVBAXZ2dlkZGRgtVjYts3vM5iRnj4kSlAAeEFQCPgmqQJyNCQRlAoB/wDeUObAgyLKzk4yMzM57LC5SJJ/Rtz27dswGo2kp0d+5S4N9IEN9jIEfxoUMTIj4kifuL3Pi7tfJD5OSXKCkpjYWGYVzkLbkRUsLDEajWSkpu+fquD10dTk9I8LGsgOaLO0QXPdUREEv9GvJCH6xAF3GAUohbDEOCEmhry0/Wm/kfCnHQdEVqGgoKCA7Oxsdu/ezeeff47ZbMZsNk/K6PmxRtrLpevTzOA9K6/XS11dXdCnLzs7m6OPPnpcDaATYbSKQFEUhxRgKBSKYNOx3W4nOTmZBSWz8ajiInZWGA0BwDfyCSg2NpbZs4twuVqorrHS0tKCyWyOqlCCP2JQBhtrB/9wBCSvREdnOw0OO52dHWRkaCguGV4oEAmBQY/NLcMHPSoGqv0Y2C+bjIqxcJBEUEoM2fwPuKXY7XZ8Ph86nY7CwkJUqv1Rb1lZKU5nE9XVFlJSmjEajeMYYCn4xVrp3wtSjtI7FQ3cXpFKeyeN7W76fSIxSgWGtDjmZKcQp1KQolYzd+5cnA4H+3bvoSkllexsAy5XK84mJwnxCfsrHCM98Q6crIWB1KDP59svWCM4pQNoEhPQpSSHdaIPlf4PDFVsa2sLDlWcM2eOv7AkiuIxllhNJbJYhUCtVuNwOLj++us57rjjiImJIT8/H61WO20fXKAiMEAg1Re4LSBSra2t1NXV0d7ejl6vZ8GCBaSm+t0Lut0e6lo6JpxnlgZcwQnTESMjQ4M6NRVbrY3t27aRl5+PTquNWvpx2L4D/h9ZU5N/Aq/X50Vn0DFrVsGoqb7Intg/6DEtNZWa2lq2bduGMTsXrU43tILSJ6FUwlRORfO7hPgFUyFAX78Hh9NfzRYXF0tOTjYajWaECxcBrVZLRkY6NTW1bN++jexACi3CCx3FwLXVBNvJxmSPswtrcw+a5DjiVQr6vCLW5h6UgkBZrn9mmlJQoNcaSIxLotpSzc6dfqPr2YWzSU1VT3z/bFBq0OcT/b1/SgGFUjnkJ6IU/NV+6ggaqEcTjLS0NI455hgaGhqG7GeFamofD6GqAaeLmbGKGYLb7eaf//wnf/rTn6iqqmLWrFmo1eohbufTRaAxOFSqz+fzBV3aBUEgLy+P8vLyYXtoSXGx5GrUExIsAf/k4Ej/XKVUMcs8C83AQMRAocJ48+0S/nElBzbW9vX1+T3qnE4SEhLIyckhQ5OBQlAgKYWwKgMjQRUTQ2FBAdp0/wiSpqZmCgqGDnqUfANpuSiWOI+EUtrv/9jV1eUfUeJqITUjjaKiItTqFMK5wFANDLDUarOCAyxNJlPYJ0EFAnj9H85YfWATodfjw97hJi0xhvgBl4d4lYL0hFjs7W4KspJIjFHQ2taOvbGRzs5OsrKySMlV09jYgMVqwWQ0kpYeJSujQalBySv6968UCgQEEmJV5KamBicfh8vgNGDopxSCptf79u3jq6++Iicnh9mzZ094Hz2cyGqq0oBT5uHhdruZP38+giCwZcuWIfdt27aNRYsWER8fT15eHvfdd9+wv1+7di3FxcXBGSz/+c9/htwvSRJ/+MMfMBgMJCQkcOqpp7Jnz54hx7hcLi688ELUajVpaWlcfPHFdHV1AbBu3Try8vJYuXIlbW1tSJLE5s2b+fLLL6P7RowTpVKJ2+3G6/UiSRIKhYLe3l52797N+vXraW9vp6SkhOOPPx6TyTTilzQpLpbcjPEVVQT2YsYdmEmQlpJKeXk5SUlJbN+xnfqGBsQIrRz8gknQYzAw96uqqoqt27bS399PcXExZWVl/oq2gNOET4z6F14xUFiiVqdyWPlhpKens3PXTmw225BIWBIHotFJQgEoRP+Gf4urhZ27dlJRWYFKpaK8vJzi2XMGhCayNSQn+wtLsrIy2b27in379uH1jt57qAT/hOWBvUN8k/fa+30i/V6JuAP2mGJVAu5+H456Jzu2bKd63z5SUtQcfvjhmMxmNJka5s6dS7Yhm337qqmqrAq7TWVMBAFBoUChUCB5JSSfSGp8LMa0VGLC2Qs7gHCrgFUqFXPmzOG4447D7Xbz6aefYrVawy7MCsVMSgNOmVjddNNNZGdnD7u9o6OD008/HaPRyKZNm1i1ahW33377kMnCX375JRdccAEXX3wxmzdv5sc//jE//vGP2bFjR/CY++67j4cffpgnn3ySr7/+mqSkJM4444whX8ALL7yQnTt38sEHH/D222/z6aefBmdnlZWV8X//93+43W7mzZuHWq3m9ttv5+WXX+avf/3rJL4zIyOKIl6vF4/HQ2xsbHDfrLm5mc2bN7N161bi4uJYuHAhRxxxBFlhjjhPio9csILiMNFzjgRKSYHJaKSkuITm5mZ27NhBV3d3eOuQ/Cc/pP0N2Nu2b2Pv3r0kJiYyf/78YD/M8NcXOHFO8DWwXzAH57gUgiLY0d/V3cW2bdtobW3df4AooYx6cDVgLOvx0dhoZ8uWLdTU1JCens7h8w/HZDKREJ8QNP4dz8cnCAoMhmzKy+chij62bNk6YLl0QD8ZQy8ihtzj8+9dRZuEGCUJsQq6PPuf1Cf6aLC30FxXS2uzE51WzxHlh5OTmzPUx1EQ0Oq0zJtXTmxsDNu3baOuttZfLBENBAGVUklOqhptUuKQveVIiFQwkpKSOOKII5g/fz61tbV88cUXNDc3R7p6YPQ04FQP7JiSESHvvvsuy5cv55///CdlZWVs3rw5ONn3iSee4JZbbsFutwejgRUrVvDGG29QWVkJwPnnn093dzdvv/128DGPOeYY5s+fz5NPPokkSWRnZ3PDDTfwu9/9DvAPVNTpdDz33HP84he/oKKigtLSUjZu3BhM6/33v//l7LPPpq6ujuzs7OBaPv74Y44++mgaGxu55JJL2LZtG99+++1kv01BDvxSKxQKenp6qKiooLu7m7i4OMxmMwaDYUL55O4+D3Wu0VOC/iquAfO9KCMpQZREGuobaGhsQK/Xk5OTizJEykOS9qf9Aqm+pqYm4uLi/P1dmgyUYY9OkECpGHfhg5JQJ+QD1yvhbHJSW1OLOtU/HTZoWaUIFD5M7D0VAE9vH/ZG/2iOxIRE9Ho96RnpozqPRGL8G4q2tlasVpvf4d1sJikpaaCwZOxHFZTgi/JXydrcw46GTgTJh7u7A5erE4UqjiNnZTHPPLTgYLTX3t3VjdVqpb/fM/6Ci0HEx6jISVcH036SJCGKfn9BhUIRdiXde++9x6JFi8ZV1CWKIjU1Nezduzfo5xfKMiwUkiTx3nvvceKJJ4ZM14uiiCAI456bFimTHlk5HA4uvfRS/va3v4V8s9evX88JJ5wwJG11xhlnUFVVFbwqXb9+PaeeeuqQvzvjjDNYv3494C+3tdvtQ45JTU3l6KOPDh6zfv160tLShuw/nXrqqSgUCr7++usha8nIyMDtduPz+Tj88MPZu3fv0CvkSSAgUB6PJ9jbJQgCnZ2d7Nq1i02bNpGcnExhYSGSJNHU1BSxFdSBjBZh7S+imIymGD+Cb2g00tHewfbt2+no7Bh6HCD4JNpa26na7U/1eTwe5syZM5CiyopAqAYe0SdGHOUIDOwJhVEtIQgCOq2O8nnlKAQF27Zuw+Fw+C8MRAaijPHnU7s6OtlTuZstW7bi6fcE054ajWZUoQL/+z6RTzQtLZ3y8nLS0lLZtXMntRYrXnd430XJR1Qi28Fo4nykia00N9bi7vNSkJ/D6QsKKTcPr4wb7bUnJSdRVlZKTk4OFouFyqoq+np7x7Wm9MR4TJlpQ/anAkVQkiTh9Xrx+XzBQqmRCNwfqZ9oAIXC39R+wgknEB8fzxdffEFVVVXI/tEDCaSxZ0oacFILLCRJYsmSJVx++eUceeSRWK3WYcfY7XbMZvOQ23Q6XfC+9PR07HZ78LbBx9jt9uBxg/9upGO0Wu2Q+1UqFRkZGUOOMZvNwU3k7u7uYJe40+kkPVqbsIMIVTAhiiIOh4O6ujp8Ph+5ubmUlJQEr2Byc3PZvXs3X331FbNnzyYnJ2fcm5wBwRocYUXqpzcRBJ+/eTcxIZGysjLsdjtVlVX7R5mjwDFQbu3t96LVav1l4rETLX/3WzOFW1quABjHOI/YmFgKCwtpa2sLzpcyF5hJTEgcKLoI/7ECVkiOBjvuXjdZ2izmz5s/jtJyhvWgRYpCoSAvNw9teiYWq5Wt27ZizDeiydQEJ/aOiA+Uiv0zscaFJNHa2kpjo52enm6MmVoWzDKijIlDpfR77I1IoKw+1DIFgSytlvSMDL/N1vbt6PV6srNzUIZRGKEUBPRpKagTQn8mgWhKGlTqLggCSqUy5G84cF6YqGAE/Pzy8vKoqKjgs88+o6ioKDiKJBQBsRotezNVxRUwTrFasWIF995776jHVFRU8P7779PZ2cnKlSvHtbjpIhAmB3qtJoNQvVG9vb3B3ij1gBeZVqsddlUVExNDWVkZWq2WiooK/ziBkpJxV9YNFixB9FsGTa5N+mD86SNBKYAgYDAYSE9PZ9/evWzZtBkkiIsfmDyr0UQYQYXBAfZIwwkMjJxYhJmWlsZh5YdRX1/Pjh07BlKe/hPgWJVyXm8/TmcTDrsdJQoMegOZmZkT/G4KA16G4yst96dCJeLjEyguLqaluQVbjY2m5qb9+2SjIIn+EnufIEaUahN9+3vFRNGHXqeneHbRiD6Uff0i3W4vKqWAOl41IBZju9WrVCpMJhPaLO2Ah+JW8vONaDQZI643TqUiN0MdVrXfYNEaHD0F0oMBoh3dqNVqjjrqKL+P56BS97S0tGHHBoR0rErEqWJcYnXDDTewZMmSUY8pKCjgo48+Yv369cOu/I488kguvPBCnn/+efR6/cBm7X4C/9br9cH/hzpm8P2B2waPoHc4HMG9Mb1ej9PpHPIYXq8Xl8s17HkUCkXQxaK9vR1gWFQ2HkL1RgmCEBzI2NHRgcFg4KijjgqO7R6NrKws0tLSohJlJcXHkpOupqG5YwqFKsDAfocC2js7abLb6e7sJjEhkb6+PhLiE0hPS4++UAUQQ5eW748wA/+aGEqFkvy8fDQaDZZqC64WF2azmdS0VL9NzwHHD56jpU5KocBoJi0tbezIJRIiFCyBwbO4hIHbBnrO0tKC0YjBYCA7O3vUz0wSpbCjS29/P3aHA4fd4e8Vy80hM13j3ysLgShJVDf3YGvpobdfRKUQyEqJpViXQlKccr9gqUZ/7YlJiZSWltDc0oLNZsPpdPjF+IAtjbTEeHTqZBSjNAKHYnBqMHDxOng/a/C5IloEfDyzsvxtCRs3bkSn0w2bsTeTeqxgnGKVlZVFVlbWmMc9/PDD/OlPfwr+u6GhgTPOOINXX32Vo48+GoCFCxdyyy23DLG//+CDD5gzZ04w7bZw4UI+/PBDrrvuuuBjffDBByxcuBAAs9mMXq/nww8/DIpTR0cHX3/9NVdccUXwMdra2ti0aRMLFiwA4KOPPkIUxWFr8Xq9wdH2W7ZsoaCgYEIpwANTfQqFgv7+/mBvVMCocv78+RF76IWKskpLS8e16ZmcEEtOppr65ok3DkeCKPoGvPocePrdaLW6YHrL7XEH3cGNRuNAM+skFHuI0pCT9mAnimiTlJhEWVkZDoeD3bt3k5GRQb4xH1VcDBIS7e0dNDY20tnZgSZDw2ElkTvhR4RPQhFGwclYqdBANBI4CbY0+30hQ121B5DEAfEbwVMvlPN5aqp60GDR0I9b39ZHZWMX8bEKspJj6fdJ1LX24RMlFuSnoVQMRFjeMPrABhrA09PSqaurY8eOHWi1OnJzc4mJUaFPTSY1cfxFBqFSg4EoK1C2PhnfeaVSSWFhITk5OVRVVfHZZ58xa9YsjEZj0GpupuxXwRRVAwawWq2YzeYh1YDt7e3MmTOH008/nZtvvpkdO3awbNky1qxZEywr//LLLznxxBO55557OOecc3jllVe4++67+fbbb4ODv+69917uuecenn/+ecxmM//7v//Ltm3b2LVrV/DEfdZZZ+FwOHjyySfp7+9n6dKlHHnkkbz00kvD1vLxxx/zi1/8gkcffZTf//73Q4QyHEaKojo7O2loaMDpdKLRaMjLy4vaCbi/v5/du3fjdDrHzEePRnevZ0oEy+1276/qU8Wgy9KRlZmJEKsYMjpCkiRcrS6sVivJScmYzNHYsxoBhRQcNTIVBMS4s6OTjIx0Onq66Pd60el06LVaYlWxEyvdC5vRKyQjFW8JCafDSW2tvxrSaDSO+pkJAvgC58UQzucGgz4Yzey31gqNKEl8Vd1KR5+XzKT9hVsen4irt59jTOlkJh/QhzhqKngovT09WK1WvG43Rx1WgjEvuiM7AqnBwPliy5YtnHzyyVF7/JFwuVxUVFTg9XopLi5GoVBQWVnJokWLQh4fmCI8VSbV0y5W4G8KvvLKK9m4cSOZmZlcffXV3HzzzUP+du3atdx6661YrVZmz57Nfffdx9lnnx28X5IkbrvtNp5++mna2to4/vjjefzxxykqKgoe43K5uOqqq3jrrbdQKBScd955PPzww0N84gJr+eKLL0hLS+P888/n2muvJScnJ6zXGKpgIlC9V19fT19fHzk5OeTm5k6av2BTUxMVFRUkJyePO8qaLMGSJInOzk7sdjttba2kpaWRrTOQkpQS3AqQAJQMm3Xk9Xqx2Wy4XK6g/VW0rzgFUUJQjL/wIFI8/R4cdod/D0YSiY+Lo3DObP++6QT3ycaDoBxuvqsQGbdgevo91NbU4mp1BWe8jVStKEoiLe1Dnc91Ol3Q+TxgrTUW/V6RT/e2oBQEkuOGJo/q2/v4njGN7LThvwkhApeR1IQ46Otm7549JCT49+3CSd2HS+B3Ul1dTU9PD8cdd9yUmMZKkkRdXR27d+8mPj4eSZI4/vjjQx57SIvVwcSxxx7L0qVLmTt3Lmq1mvz8/FGPD9UbFRgl0tjYSEJCAnl5eej1+ikJraMRZUVTsPypvhYcDgdutxutNgudVkdCbFzIE6FfsEKP+Ghra8NisRAbF0uBuSAqIxICprzBf0+gUi4cunu6sTcOWCGpU9Hr9SQlJVFXV0eTw0F2bg6G7Owxy9AnhYEKSQX4Wxei0Mzb3tGO1WpFEATMZjMpyftP7D6fD+eA87kggC7bQGZW1pDqO4XkL3IJ5yssSRIbbG20dPWjHRRB9XlFOvq8LDSnkZ4U2uFFEEavUlQIwpC0n9frxWKxUFNTQ05ODrNmzZrQyTsw3cFqteJyuTAYDOTn55OYmBisGvSvc3JFq7+/ny1bttDS0oLRaKSwsHDY6xJFkZiYmCnb15LFagTOOOMMzjzzTI477jji4uIoKCgYdsxIqb7AKBGXy4VOpyMvLy/qAxnDZaJR1kQFy+Nx43A4cTqd/vz+wFA/lUKJ5B395DOaYPl8Pmpra3E2OcnJycFgMIzvxC5J/v2PEHOnBIUQVU87SZJobWvFbrfT1dVFVmYWer0+KLb+gg6Jzs4uqqurkRRgKjCjTomOKWnY60RCKUR/srEoiTQ2NtLQ0EBGRgZ6vZ6WlhacDr+Po96gJyMjw7+XpBCCGjlW2i8Uje19bK7tQCFAcpyKfp9Ie28/Rk0C83JTUYz2xRMExBBVinEqFTnpKcTFDD85d3d3U1VVRUdHB7Nnz4744jCQfbFarXR3d5OXl0deXl6wOG1wanC0UvdoUlNTQ2NjI0qlkvb2dmbPnk1eXl7weX0+H7GxsbJYTTc/+clPOPzwwzn77LMRBIHZs2cH7xurN0qSJHJzc8nJyRlXD0y0mWiUFalgSZIUNFFtbXWRlpaGTqdHrVYjCP6G2HCHEo4mWIA/VWKpRiEoKJhVQFJieN35sL/ZeLSVREOwAg7wgVSfTqdDp9UFf+TSkPJ4P5Io0Wi3U2evQ5OZSX5e/pScFAQYmLYsRV2sA7S2tWKxWOj39JOQmIDJZPLbYw1JeUoD454Dq4oMSZKob+/D2txDl8eHSiGQnRpHQVZy0PB2VIShE5dTE+LRp45e7RcQnKqqKmJjYykuLg5OPBgJUfQLuNVqxefzkZ+fT25u7qgWR+NxwRgP1dXVdHR0MG/ePJqamqisrESpVAanFMtiNUO46KKLyM7O5he/+EXQGNXn8w0bydHd3U19fT0Oh4PU1FTy8vLIysoad8f5ZDKRKCscwRJFf9Oq3W7H7XaTlZWFTqcLPk9AHCJFAhh0pT3seSWR+rp6Gu2NGPQGsnPGKJkOIQ6joYiweTeA2+3G7rDT5GwiPj4+aAs1NAKUBlzsQ6/F7XZjqbHS1dONyWgiQ5MR3dL1QRyYCoX9+zgTfU4Jifa2dhrt+53PExMSaWhsIDYmFpPZNORCQ8FAv59SgTQBt3qvKNLnEVEpFcTHRPibFAAl6FNTIqr28/l8WCwWbDYbBoOBwsLCYcbS/f391NfXY7PZiImJwWQy+ffzwjhvBKoGD+zNirZo7dmzB7fbHSxiE0URm83G3r17ycrKYvbs2aSmpk5ZxaAsViPw29/+FqVSyaWXXkp3d3ewUCPwhWhpaaG+vp6uri4MBgN5eXkTGug3VUwkyvILVvuwlEwg1dfU5ESlUqHT6Q9oWpUiiqZCMZZggX8fyFJtwefzYR4lfaYQIzfhjCTKCBSQuFpdpKenY9AbSE4ePmgveEIeA0mClrYWrDU2khKTMJvNUY3YpTE+n4kIljjgutHY2Ei/p98/iVenJWZg4KNP9AUb4XVaHbk5OcQoVEM/H9XIkfVkEqtSYtCkEB87vj2onp4eqqqqaG9vZ9asWeTm5uLxeKipqaGuro7k5GRMJtO4J2gHBAuYlNRgRUUFACUlJUNud7vd7N69m97eXo499lhZrKaba665hubmZm655RZqa2uDkUhjYyP19fXExMSQl5eHwWCYsmqYaDLeKCsgWKLoT/U5HA5crhZSU9PQ6wOpvgNOyiITmCuyn7FSguA/Odrtdurq6tBmacnLy9u/KS3BRDZiRjtpi5JIq8u/H9Xb20tWln8/KpSo7DfljWwtXsmHrbaGlpaWMSvrIkEhSmN+PIJCwEf4ZhNerxeH01/lqFLt36scKeLt6e3BZrXi7u7DaDSSnp4x9LkmGGFFSkpiHPr0lIibfEMR+K0FpihkZmaO2X8WCYNTg4GMTzREa8eOHcTFxQ3ZAhn8nF6vl4SEBFmsppszzzyTTz/9lOeffx6Hw8GXX37J+eefT1ZWFnl5eQMbwVNfMBFN+vv7qaqqoqmpKewoSxRFLDV1bNm1j97eXrRa7ZBU32AUgb2PKK5ZkgjrSruvr49qSzXuPjdms5mM1LQJRXYBDhQsr9cbrGRTCIqgM8BIP2ABv5HtuEMFpUB7ZwcWiwWFQoHZZB53RB9uZBdAEPzp0NG+In19fdjtdpqam0hKSsJgMITluqEARK9Ec3MzNTU2kpKSMJlMQ79XytEj62ggCALatCTSkideYQoEK/taWlqCRgMGgyEqgxEHMzg1ODjKmsg5auvWraSkpIQsLgs8V1xc3JRtechiNQKtra1cfvnlrF27FpVKxc9//nN+9atfERcXx9y5c8O22T8YCCfKcrvd1NXVUVdXh0qlIlOrx6dKGuGkPNixPfpIEgiqsUvLJUmiydlErdVGeno6xnwjqhCVXJEiCALd7h7sdseQk3J6WvqoJ4dIxWFElAK+QaNVdANuCuFe4Y43soOBYiLF8P6vrq4uGu2NuFwuNBkaDAZDWL+RwQUdAbxeL7W1dTQ3NwVtmwInREE5OUUf4E/7ZWvUxMVO7DsiSX7RtVqtdHZ2kpubS35+PvHx8cGBqS6XK5gajObJfnBqMJTXYCRs2rSJzMxMjEbjiM8ji9U084c//IE1a9ZQWlrKeeedx7/+9S+am5t58skn0Wg01NfXU1hYOKSM82BnpCirvb2d2tpaHA4H6enp5OfnBx03Qu1h7W/cnNyvVTiCFRAHj9vjP3F0dWIymdBkaMbXayv5bbwa7Y10dLaTpgn3pOwX72hEdgECfWC9fb1YLBb6+vowmUxkpGeM/nf4P5+J/OwDgiXBgPN5Iz09PWiztCOmPkdey8gpyK6uLiwWK6Low2QyBSvrBIUwpFIvGkQj7SeK/hS0zWbD4/EEK/tCbRM0NzdTVVWFQqGguLg46hMdolHqvmHDBnJyckIaIshiNUN47bXXMBqNfO973wP8V3qrVq3iT3/6E1deeSW/+c1vgpNpy8rKpmz42FTQ1NTEzp07iYuLQxAEenp6yM7OJi8vL+RJeb9gSRE1bkaDkQQr5AlZghZXC1arlZTkFP8wxLjw0jCSKA14F9rx9HvQaXVotVri4uPGTIuFUx4/bgb27yT8JdM1tppRrY2iFdmJokhTcxONDgc+yecvmsjShl3CLCGFPaxRksDh8O9BpqamYTTmExsbGzXBEgSBrLQk0ieQ9vN6vdTX11NTU4NCocBoNGIwGMaMdAPVdRaLhaysLIqKiqJbODPBqsH169cHfVdHeuz4+Pgpu2CXxSoCvv32WxYvXoxCoeDJJ59EpVLhdDqZM2cOBoPhoI+y3G439fX11NbWBt04DmwEDEV3r4fGpg6kaI0Dj4AD97BClV8PxtvvxVZjo7W1lfw8v2XTSFGWt9+L3WHH6XAOKRJQKPefJUfbx4la2m8UBjtt9Hv7sVlttLW1kZeXh1anHdgrik5kF3g/HA4HsTGxZOdkk5Z1YCn+GOtleNovHPr7+7HZbLS2tpGXl4tOp0OhVPj3D8f5u4tRKsnOHH+1X6Cyr7a2lsTERP9IkXFYgPX19bF7926am5spKCggPz9/0lKDkbhgfP7558yZMyekabksVgcBfX19/OEPf+Cxxx7j1ltv5ec//zlVVVWkp6dTUlIS1U3TqaKjo4Oamppgqi8vL4/MzEyam5vZtWsXKSkpY1YMdve4aXB0MEWuq0MIRFhEcBJsa2vDarESFxeHucA85LX1dPtHc7S0tJCiTkGv15OWmjaiqB1YKReNVFskHGgN1d7ejsViISYmBrPJRFJ8EhP5XPp6+wY5n6dgMBhIVafCgEhLivBKy8e6kAiH9na/bZNCocRsNpGiThkzug1FSkIcuoxklOMQhZ6eHmw2Gw0NDaSnp2MymUhPH32/MhxcLheVlZUAFBcXBwe/RotIU4OffPIJ8+bNC5miDBgiyGI1w5EkiU8//ZRly5aRnZ3NI488Qm9vL21tbZSWloY1PmW6EUURp9Pvit3Z2Tlir1gkFYPTJ1iCv/xaEBAjKG8OWDY1OZvIyckhISEBh8NBZ2cnmZmZfiukxPDSQ4F9HCHM9Fa0ObAPzCf6aKyrp7He3yidk5sT2dW6BB2d/lElHe0daDI1GPSGEd8PSTmKs0OETdhjLk2SaGhooKGhgczMTPKN+ShilGErljY9eVxpv46ODqxWK06nE51OF3TeiCaiKFJbW8u+ffvIzMwcNmMqGoTrgvHhhx/yve99Lzg5/cB1CoIQ3C6YCmSxmgAdHR3ccMMN/OMf/+DPf/4zp556Knv27EGr1TJnzpwZNbgsgMfjCab6FAoFeXl5ZGdnj9kr1tTUxK5du1Cr1ZSUlIz4A5pqwRKkwOiKAZSKiARL9InU1tXisPuHe2q1Wr/dTaRVg9JA5CBMR2zpZ3+EtT/t19PT47c26u/3D3ocw/5HEv3jWBobA87n+gHn8zBSZSF74CT/ZzQJlaF9fX1BLz2jMZ8MbRbCKAUS40n7SZKEy+UfT9PW1kZOTg5GozEq5smj4Xa72bNnD06nE7PZjNFonJTU4Gj7We+99x6LFi0KOR0iIFZTuV8vi9UEkSSJt99+m8suu4wFCxawevVqmpqa6OnpoaysLOqh/Hjp7OykpqYGu91OWlpa0BYqkquicKOsKREsaZS0Uhhl7R63B4fDgcPpID4uHq1W67dHstsxGAz+icvhVoZJ/sZaBiq6RYUw1ZM99iMM7AkdsD6H00FtbS1paWmYjKZhYuzz+Why+v0LERizX2xElOHvH0YDSYLWVhc2m424+DiMs8whT66Rpv0CmQer1UpfX1/QWHaq0/ytra1UVlYiiiJz5swhMzMzqo8/kguGKIq8//77fP/73w9Z9BGIzKbS+1QWqyjR1NTEFVdcwbp163jooYc4/PDD2bt3L3l5ecyaNWtaJm6KouivEqupoaOjIzhuYKK2UOFEWZMqWJK/5HnUhx5BsAIGu64Wv8FuwHUjIC493T1UV1cjiiIFBQUkp4z+XikAvAcsJJCSm2LBUkoBP73QvUgejweb1UZHZwf5eflkZWUF52k5nA4SEhIwGAz+8veJrF0pjKuIYiL4fAO2TQ4Huhw9OTm5KAcKYbRpyaSnhBcJ+Xw+GhoasNlsSJKEyWQiOzt7WifmiqJIXV0d+/btIz09nTlz5kQ9shvcUCwIAj6fj48++ohTTz01ZIZIFquDHFEU+fvf/84111zD2WefzR133BGsrAvMxZoKAqm+uro6APLy8sjJyYmqLVQ4UVa0BcvfzCqEX3U4IFiSKPn7geyN9Pb0kpnl348aKYUhiVLQVitLmzXEsmn/QQPiMNIJWfDv40zFjytQYXfgPK6RzHdbXa1UW6oRBAGv1+sfgGnI9l/ETFBgg2bFo0wdnkx6enqwWK24vR4KZxVQWphPYvzY0ZDH46G2tpba2lri4+ODlX0zyZDa4/GwZ88e7HY7JpMJk8kUVREdnBr0eDx8/vnnnH766SHfA1EUUSqVUxppymI1CdTU1LBs2TJ2797N448/jtFoDE5JNplMk/YD6OzspLa2lsbGRlJTU8nPz4841RcpY0VZURMsab99U7h4vV6aWltotNsB0Ol0ZGmzwt5L7Ovto7q6Go/Hg8m838tNITFgmTSWoZ6ApJzcPSwF+EUq1JMcGGFJ0Nbehr3RTmdnJ3HxcfT19ZGdnU1OdgRpz1HWIvkkgluGqukRLEmCnq42WlvqSU9Lo7i4eMRIpLe3F5vNRn19vT9FajLNeCu1trY2Kisr8Xq9I5aWjxdRFGloaMBqtaJSqTjmmGNCumDIYnUIIYoijz76KL///e9ZsmQJy5cvp7q6GqVSGVW7psAMnZqaGtrb24NVfdGuUhqNwVFWqJ6ziQqWwAEnwTEI+tM1NZGQmIAhN4e09PTxnYwD+z01taRnpGPOM6IaZfzI8MVPnmApDiwuCYVSwCuJuFr8RROefg96vd4/TytGRVdXF1aLFVESMZvMpKjH971RHBDZBQlj/zCaCIJAZkYS6epEPB4Pe/fupbGxkYKCgiFFCp2dndhsNhwOB1lZWRiNxjGLT2YSkiRRX1/P3r17SU1NZc6cOSH36sLF5/NRV1eHzWZDpVJhMpnQ6XTA/nFIg0XL5/OhUqlksTqUqKioYPHixXR0dPDUU0+hVqujYtcUmIdTW1sLEBz2OJ19XqNFWeMRLEkKRDHhOB1IdHZ10djYSFtbGxnp6RgMhv37cxFWCR6Ix+3GWm2hu7N7wNYogr6aKBddCAyMORnjffE7nzuxO+0oYlQYDAZ/U/MBkb0kStjtdurr69FoNOTl54VfySqF4ao/wfc+XGJUSvRaNQlxQ9PdbW1tQdfz3NxcWlpaaG1tJTs7G6PROKGT/HQzWJCNRiNmszmi1GB/fz+1tbXU1NSQkJCA2Wweko0ZqWowMNJ+KidOyGI1BfT393P33Xdz7733snz5ci6++GJ27949Lrumrq6u4LhptVodTPXNlNz6aFFWRIIVThEFIEoSLQNWSG63G61Oh06nIy6UaI/zKj8QwUiSREtLCzabjeQUv2VTyOcZAUmlYKLGS6Om/QZwu900NjbS1Ny83/k8Iw1JGF0w3W43FouFnp4ejEbjmB6Kw9J+ozHJgpWUGIc+KyVktZ8kSTgcDvbs2UNfXx/JycnMnTt3SrMPk01HRweVlZW43W6KiorGdNJwu91B9w21Wu2fTDBK+vPAqkFBEGSxOpTZsGEDS5YsITExkSeeeAIAp9NJcXExer1+1C9KU1MTtbW1tLW1odfryc/Pn9E/tpGirHAE68BigVD09/fjdDqxOxyolEq/FVJW1tilyZEIljRIHA54bpvNb2uUbzSSFcHwvIkI1oiptgH8zud2XC4XGRkZGPT6IZWfAT+9UZ99wEPRZrORmJg44qDHsFKQBzIJgiUIApnpSaSnDo+OfD4fjY2N2Gw2fD6fX4A1Gvbt24fL5aKwsJDc3NwZvT8VCYFm6T179pCSkkJxcfGw7Ybe3l6sVisNDQ1kZGRgNpsjmqsVqBK8//77WbJkCcuWLYvyqxgZWaymmN7eXlauXMlf/vIXbr/9dv7nf/5nRLum/v5+GhoaqK2tRRTFYFXfwWLpNFKUNZJgSWNV2AE9vb3Y7Xa/9U9yst8KKS0tshNOGBv/4aTaWltbsVitJMTHYzabw4uQx1MlKIFCkgilshIHOp+PPPTR//zh7aF5vV5qa2qHDHoUFMKoawkHQaHAp4jOKWektF9/fz91dXXU1NSMODK+ubmZyspKYmJiKC4uPqj2q8aiv7+fffv2UV9fT35+PmazOdhA7XA40Gq1Ebtv+Hw+3nnnHVavXk11dTVXXXUV1157LRqNZhJfyVBksZoGJEni448/ZunSpRQUFPDwww/T2dlJe3s7paWlJCQkBKv6UlJS/KakM6yMNhKcTicVFRVDoqwDBWuYE8UgJEmivb0du91OR2cnGo0GvV5P0gT2GkYr7Y4kveXz+aipqaG5uZnc3NxRI+T9T87+Xqwx8DtRiMPW4hNFmpv8Tbw+URxwPg+z0lEB4hgpwQCdHZ1YrBYEBGYVmElKSAq70GVEojCTKikxDn1mSrCXCvyFNYGR8SkDadrRRsb7fD6sVitWq5WcnBxmzZp1UE79HonOzk527NhBT08PkiSRnZ2NyWSKaI+uv7+f1157jQceeACXy8X111/P5ZdfPmVtOIORxWoaaWtr47rrruPf//4399xzD729vbz//vtcdtllGAwGjEbjtHwpJoNQUVZPr4cGR/uIQuUTxeBoDm9/PzqdDq1OR2yUTijDBGuEtF84tHd0YLVYUCqVFMyaReIYTZuSwAj2RPvXomS4a3u/14vD7nc+j4mNJdtgIEOjQRFpKiuCCE8UJRwNDdTX1qPNGqHvLFIC1lCRLlsQ0KQlkZG2/4Tb1dWFzWbDbrej0WgiHhnf3d1NZWUlXV1dFBUVhXfBMYORJH9focViob29nbS0NDo6OkhOTqa4uDgsU4C+vj7+/ve/s2bNGiRJ4ne/+x3Lli2bdJup0ZDFapppa2tj+fLlPP/886hUKn75y19y4YUXBhuJoz2Ubbo5MMry+sDe2DGkmszT34/DbsfpdBITG4ter0ej0YzLIXtMBq7yBQR/QccEXBd8ouh3UbDbyTYYyM7JGVVERhKsYGPtoDt6+/Y7n6tT/M7n6tTUiRUYhpESHPy+9Pb1HTDocWLfTUEh4IvgI1UpFRi0qSTE+y9WBo+M1+v1mEymcbeEBIowqqqqgif1g20aeGBvO+CXmJ+fH7SI8nq97Nu3j7q6OnJzcykoKAgZRXZ1dfHXv/6VRx55BLVazc0338yFF144IyJOWaymkTvvvJP77ruPuXPnctFFF/HOO+/wzTff8MgjjzB37txpt2uaLA6MslJSMnA4OugesEJqcblIVauDVkiTfZUrKKI7xbe7u9tv2SRJzCooGPNKVho0j0uBAN6AHa2/ysve2Eh7R0dU0p/DGKWsPlQRhYR/v6dmnBWRw58kvCGKiQmxGLLUKBRCcGR8V1cXubm55OXlRc1QdfBJfTyl4NOBKIo4HI6gYbHRaPSbMYdICXd1dVFZWUl3dzcZGRmUlZWhUChobW3lqaee4vHHHyc/P5+VK1fyk5/8ZEa9dlmsppE333wTvV7PUUcdBfi/dM8++yzLly/nvPPO43//93+xWq1Tbtc0VTidTnbt2kV8fDxut4+G+tb9ozmmJN0gBYsoBJUiqs2rorTfskmn1ZKblzd6ZBgYseGTECWJVtd+5/NRy/GjgQCSclCV4ggpyMH0e73U2Gy4WlvJy81Fp9ePP8pTCEgjVCkKgkBGWiLp6gTsdjtWq5X+/v5RR8ZHg8Gl4MXFxTNy7E+g2tFqtQJgMpnCmlAciCIvuOACOjs7mT9/Pu+88w7z5s1jxYoVnHnmmTNyf/yQEasnnniCJ554IvjBlZWV8Yc//IGzzjoLl8vFbbfdxvvvv09NTQ1ZWVn8+Mc/5s4775yRVUDV1dUsXbqUmpoannzySbKzs6fErmkq8Xq9QcNQj8cDQE6OEZVy6srxBVEcUtUmKBUT3vg/kN7eXqotFvo9nhFHdAgAoohPknAMFE0ITMD5fDwIgZlUkaVDBw96NJnN44/6QqQkVUoFmemJtLqasNlsKJVKjEYj2dnZU/IbCLhE7Nmzh4yMDObMmTOlIzFGwuv1Bt0mYmNjg24T4b4nkiRRW1vLfffdxwsvvIAkSZx77rk888wzM3rb4ZARq7feegulUsns2bORJInnn3+eVatWsXnzZiRJ4rbbbmPJkiWUlpZis9m4/PLLKS8v57XXXpvupYfE5/OxZs0abrvtNi699FKuu+469u7di0qloqys7KDLpwfo7e2lpqaGhoYGEhMTMRqNaLVampubqaioICYmkbRU/aSW5yskRjTDnQzBkiQJp9NJTU0NGRoNxvz8YIpGkMDd24vD4cThcJCYkojOkO1v0IzuMsZEEMa2OwzF4L06vV5PTk7O+PYXBRAHIkyVEvr72miorycpKQmTyTTpPpcj4fF42L17N06nc1LGzkeyjoDbRFJSEmazedRqxwORJIk9e/awZs0aXn31Vc455xxWrFhBSkoK1157LZs3b+b111/nuOOOm+RXMj4OGbEKRUZGBqtWreLiiy8edt/atWv51a9+RXd394wckhhg+/btLF68GI/Hw5NPPklSUhL19fXMnj37oGloDJSe22w2mpqahnixDV5/YC+rttZOepoBjUYT9denkKSxJ9aqFJPi5RdwiOju6cFsNJIQH09jXYN/jy41lexsvz2UEKMcl2iMF4lA75SEJIGgUo6rcbm7pwfrwL5JpBV5Afrcbjq7W+jp8jc2Bx5nJnzPW1tbqaioAKCkpGTKopC+vr6g2W5qaipms5n0COy+JEli+/btrF69mrfffpuf/exnrFixgtLS0iG2Sv/+979ZtGjRlPZORcIhKVY+n4+1a9eyePFiNm/eTGlp6bBj/vKXv7By5UqampqmYYWR4fF4uOOOO1izZg0333wzixcvpqqqalx2TVNJYOO3pqaGnp4ecnJyyMvLG3M/yul0snnzdrz9/tRSNPZq/IMAxfCtCSdJsERJoq6mBntDA4iQmZlJdk728PdEOTnPPwwhUHm4/9kkCYQYxbgEUwKcjv2DHo0mEzFhXAx2dXXhcNgRpW7y8vyefTPRoUUURWpqaqiurkan0zF79uxJywL09PRgtVppbGwkMzMTk8kU0baFJEl8/fXXrF69mk8++YSLLrqIm266CbPZPCPEP1IOKbHavn07CxcuDPp/vfTSS5x99tnDjmtubmbBggX86le/4q677pqGlUaOJEmsX7+eJUuWoNFoePzxx/F6vWHZNU01AQeB2tpaFAoF+fn5ZGdnRxTB9vf3s3nzdqqrGzHmGyNKdwwmGDWMo3cqmkUXQQ/DxkY8vX1kZWnp6+ujs7MDo3GE1zfJgqUQQOwXCfW2+iOs8T+/2+PBZrPR0d7ut6TKyhqW1pSA9rY2Ghob6ff0UlJqwmw2TWsvT7j09vZSVVVFa2srs2fP9k+WjtLvr7OzE6vVitPpRKfTYTKZIhqYKooin3zyCatWreLbb7/lsssuY/ny5eTk5ERlfdPFISVWHo8nOCrjtdde4y9/+Qvr1q0bEll1dHRw2mmnkZGRwZtvvjkj+gcioauri5tuuom//e1v3HXXXfzgBz+gsrIypF3TVNPd3R3cj4rWPC2rpY4NG7b79y0ijLL8hQsT652aqGAFnM8djXZUCgV6nZ7MzMyg84LL1YrVaiUhIZ4CcwFx8UNtkgSVYiLLD4lEwNYqjFemGl+EFaB1oBcqNjaWgoICEuLjESUJV0vLgEh5KJpjYu7c2QfdbxH8HpiVlZXExcVRUlIyoWiwra0Ni8WCy+UKuk1EItw+n4///Oc/rF69mn379nHVVVdxzTXXkJmZOe41zSQOKbE6kFNPPZVZs2bx1FNPAf4rljPOOIPExETefvvtGZs+GwtJknjvvfe45JJLKC0t5aGHHqK1tTVo1zSVZbaSJOFyuaipqcHlcqHT6cjPz49qmX1baxdffb2Vtta2kaOQAxAAyStGpUhhPEUXQefzpiaSk5IwaHUj7r14vV5qamppaWkmLy8PnU439LhoRlgh0n5j/olyYoIdmJVkdzhIVavp7etDAHJys5k7t5CUMEfOz1R8Ph8WiwWbzUZubi6zZs0KO4sQ+P1YLBY6OjrIy8sjPz8/onHxXq83aInU3NzM9ddfzxVXXHHItboc0mJ18sknk5+fz3PPPUdHRwdnnHEGcXFx/Oc//zmoZ9gEcLlcXHXVVfz3v/9lzZo1HHvssezevRudTkdRUdGkFo74fD7sdjs1NTW43e5gc2YkP7JI6Orqo2KXlWqLheRRoqyJpP1GRSn4R2yMuU7/TC1Xayvp6enkGPQkJ4RXudne3oHFUk2MKgZzQQGJiYNO4lEQrKCAj0fBJ/D8AYsou92OKEmoVCrmlhVTNCcPlWrmNJ1OlEDDbU9PD0VFRcMvOgYRqBANOIIE3CYiiS7dbnfQEsnn8wUtkQ6Fc1soDhmxWrlyJWeddRb5+fl0dnby0ksvce+99/Lee+9x9NFHc/rpp9PT08Prr78+pOx7yvpYJglJknj11Ve58sorOeWUU7j77rtpaGigr6+PsrKyqFcsud1u6urqqKurIyYmhvz8/LAaEaNBV1cfdbUtWK1W2tpCR1kH9k5FlREES5IkWtva/M7n3d1otVr0eh3xMXER14L7fCJ1dXU4HA6ysw1kZ+egGJhwPJEIRyFJE3fpiFCwAtGls6mJlJQUsg0GklNS6Otrp7m5Hr1eT1FR0UGZ/hsJSfIPsty9e3dwTMdg8RBFMdjc7PV6MZlM/lL/CH4/3d3dQUuk5OTkoCXSwTKNYbwcMmJ18cUX8+GHH9LY2Ehqairl5eXcfPPNnHbaaXzyySd8//vfD/l3FosFk8k0tYudBOrr67n44ovZvn07jz32GHPmzImqXVNnZyc1NTXY7XbS09MxGo2jDmubLLq6+rDbO4Kpk+SkJMwFBcTFxARtiiaTwSnBkZzPY2JUSCMULoRLV1cX1dUWAAoKzEMmHkfygw00HEcrjxiOYHb39NDY0BCMLrMNBpKSklAqFej0ahIT4+jt7aWyspKOjo5Dwjz2QPr7+9m7dy8NDQ2YTCby8vKw2+3YbDYUCkXQbSKSfq22tjaeeuopHnvsMfLy8li5ciXnnXfeQX2xHQmHjFjJ+K/annrqKW666SYuuOACVq5cicViQRTFcdk1SZLk94GrqaGtrQ2DwUB+fn5ElUmTQUCw+j0ebFYr7a1tGPPz/VHWFLTSekUvjU5n0PncoNejGYjwlITRxxUmoijR2NBAfUMDOp2O3NxclEpF2BFWsFw/2oQQzICPYWNDAx2dnWRlZWHQ64P7wvEJsej16iFpv8HmsaGikEOBlpYWduzYgcfjISEhgcLCwlHTg6FwOp08+uij/N///R+HHXZYMIt0KDjZRIIsVocge/bsYfHixTQ1NfHUU0+RmZmJzWajoKAAo9E45pfc5/PR0NBATU0NXq+X/Pz8GTf0saurD2djB5LPNxBlWQeiLDOxMZOzzt6+3v3O52mp6LOzhxjtCmJkhQvh0tPTi6W6mn5vP2ZzAampagTF6EUfUUn7jULg+SX8e6eNA6lnnV6PXq8f0luVnp5EhiZpxBN0f38/e/bswW63Yzabw/qOznQClcm1tbUkJyeTnJwc7JcqKioKq7irtraWhx56iOeff57jjjuO3//+95x44omHVAQaCbJYHaJ4vV7uu+8+7rrrLq688kp++9vfsmfPHmJiYka0a+rr66O2tpa6ujoSEhIwGo0ReY5NNd2dfdjrW0GCfm8/Nqt/1LzRZIxalCUh0dHROeB83o5Gk7nf+VypQBImWLgQ7joGopDa2lo0mkzy8/OIiYsNGWEJUUz7jYTPJ9Lc6i8/lwBDCB9DpVKBVqcmKSm8opu2tjZ27dqFIAiUlpbOSN/OsQhM5K2vryc9PT3oNgH+Pbzdu3fT1NTErFmzyMvLG/bbkiSJvXv3smbNGl555RXOOussVq5cyfe+973vrEgFkMXqEOfbb79l8eLFKJVKnnrqKWJjY4fZNQWskJxOJ1lZWeTn588Yi5uxGCxYAK7WgSgrORmz2TTuKEuURFpdrYOcz7XodPohFYgS/sbaqfwBufvcWKwWurt7MJvNaLIyCBToCxL+/alJxOv14nA4sdvtxMTEkJObTVpm5rC5XfEJseh0amJiIttPEUURq9WKxWIhJyeHwsLCGW2HFqC7uxur1YrdbicrKwuTyTRi2t3lclFRUYFCoSA1NZXS0lIkSWLHjh2sXr2at956i5/+9KesWLGCsrKyg+J3OBXIYvUdoK+vj//93//l8ccf59Zbb+WXv/wlO3bsoKWlhby8PLq7u4NWSAfjnsGBgjU4yjKZTGgyNWFHWT6fD2eTc8D5XBjF+XygPF6SEFQCkjB10WdgL9Fms5GamorJbCImNm5Shcrt9mBvbMTZ5CQpKZnsbMN+b0eFgCjsf4fT0hPRaJIndJINTO/t7u6muLgYrVYbnRcSZTo6OrBarTQ1NUU0AFIURbZt28bpp5/OggULiImJ4YsvvghaIhUUFMgidQCyWH1HkCSJTz/9lIsuugjwnwwMBgN33303c+bMiapdzHTQ1dGLo6FtSJgTSZTl9nhwOOw4HU7i4+MxZGeTnp6GIoQICUhIB1QeTrVgAXg8/disFjpa2zCajWiytFH/DHt6/Pt0LS0tpKWlBc12D0RQCKBUoNOnhp32GwtpYCbY7t27SUtLo7i4eMY08gfGxre2tpKTk4PRaIzIbUIURT799FNuv/12Nm3aRFxcHHfeeSfXX3/9jE27TzeyWH1H2LdvHw899BDPPvssiYmJdHR0cN9993HOOedQWVlJRkYGxcXFM6qIIlJCCdZYUVZ3Tw/2xkZaXC2kpqZhMOhJSUkZIRKTEEZxbfeXtQuTunc15PmQkPp9uFpbsVosJKUkYywoiMoJvaOjk8aGBto7OsjMzMRgGH0gZlx8DLqcNGJiop+yGzyio7CwkLy8vGm5sApEtIEpxQG3iUh+M6IoBi2R9u7dy29/+1uuvfZaPv/8c6655hpMJhP//e9/D9oRQJOJLFbfAURRpKSkhAULFnDdddfxve99j7feeovLLruMI488kvvvv5+WlpZpsWuKNqEEC4ZGWSaTid6eHhrtjXQOlFnr9XoS4ke7MpYQfOKYxX5TIVgSoBDFIaLpt2yy0dLWSm5+/rj6liRJorW1jcaGBnr7etFqdej1emJjR2/aTU1PQqNNmXQBaWlpGZh5FkNpaemUubIHilssFgsej2dcU4q9Xi//+te/uP/++3E6nVx33XX89re/HVJE0tXVxT//+U8WL148GS/joEcWqwgZbSLxYCRJ4uyzz+a///0vr7/+Oj/+8Y+nfrGDcLvdw6yQmpqauPzyy/n00095+OGHOfLII6fMrmkyGUmw3B4Pe3bvpru7G4VSgUFvQKfXEaMa/aTjT/v5IMx9L0EpIAqKSRGsQOXhSKrZ3t6OpcZKTFyc3zg2jNSUKPojhsbGRrxeLwaDAZ1Wi3IMKySFQoHWkEpSytSl5gb78EWr4X0kRFEMjo0XRRGTyUR2dnZEz+d2u3n55Zd54IEH6O/v54YbbuCSSy45KPeGpxtZrCJktInEZWVlwePWrFnDBx98wLvvvjsjxGokRFHkxRdf5Nprr+Wcc87hj3/8I3V1dZNm1zRVDBasgPO53W5HpVSiTlXjanGRnJIy6l6W32dQHFeT72QIliCB5PUylmiKoo+6+nrsTU3k5OYOOCUM/xuf1xd8X5RKJQaDgczMzJDHHkhc3EDaL3Z6Lmi6urrYtWsXbrebkpKSqDqL+3w+6uvrsVqtqFQqTCYTer0+or2k7u5unnvuOR5++GESEhK4+eab+fWvf31Qp9mnG1msosCBE4m3bNnCD37wA7755hsMBsOMFqsANpuNZcuWsWfPHp588knMZnNU7Zqmg2ZnK1u/raSpqYmkpCQMBoO/JB9hzL0sQRgoopjAryNaghUq7RcO3T3d7LVYEBQKZhUUkJTs3wfxePqx2+04nQ4S4hOCxSThpvGmKu03FpIkUV9fz549e9BoNMyZM2dCRsr9/f3BsfHx8fGYzWa02siKVtra2vi///s/Hn30UXJyclixYgU//elPD9osxUxCfgcnQGAicXd3NwsXLgT80z1/+ctf8thjj6HX66d5heFjNBr54IMPeOSRR/j5z3/OkiVLuPHGG9m3bx8tLS3MnTt3Rk5uDcXgvrGU1DQyM0tIThpawRajiqGwsDC4l9XicgWjLH/hwsTLwCWfhEIpIjJ+wRKQwDv2XlkokhKTKJ9bRn2jnZ27dpGZmYkkSbS0tJCqVlNUNIeUlPBLzBUKBVl6NcnqmTHSQxAEcnNzycrKoqqqii+//HJcgxDdbnfQbUKtVnPYYYdF7HvZ1NTEY489xtNPP01paSl//etfOeecc+TKvigiv5PjYPv27SQnJxMXF8fll1/O66+/HhzweP3113Psscdy7rnnTvMqI0ehUHDttdeyceNGNmzYwJlnnolKpUKr1bJhw4agz+BMJDByYePGjcFS4OOOO46jFx7JrKLcETNnGekZlJcfhkIhsG3rVlqanIj9vuityyf5U4njEBtB8lf7TSi6kwTS1SkkJyfT5HTicrVgMpmYUzwHtTr86CguLoZck2bGCNVg4uLiKC8vZ+7cuVgsFr755hu6urrG/Lve3l4qKir4/PPP6erq4ogjjuDII49Eo9GE/b7U1dVx0003UVpayubNm3n99df54osv+OEPf3hICNVdd93FscceS2JiImlpacPu37p1KxdccAF5eXkkJCRQUlLCQw89NOLjffHFF6hUKubPnx/xWuTIahzMmTOHLVu2BCcSL168mHXr1rF3714++ugjNm/ePN1LnBAlJSV88cUX3HXXXZx55pnccMMNXHrppVRVVdHU1DSiXdN0MNjH0OfzkZ+fz/z584dUagVOsKGKLsAfZRUVFtLsbMJmsdKS3IzJHD2PwYgjLMlvmeT39htfSCYh0d7WTkNjA93d3Wh1WgoK5tHa2orN5i+9zs/PCys9pU5LJFOnnva031hkZWWRnp7Ovn37+PrrrzGZTJhMpmEp7K6uLqxWKw6HA61Wy1FHHRVR1kCSJPbt28eDDz7Iyy+/zBlnnMGHH37I0UcfPePfo0jxeDz87Gc/Y+HChTzzzDPD7t+0aRNarZYXX3yRvLw8vvzySy677DKUSiVXXXXVkGPb2tq46KKLOOWUU3A4HBGvRd6zigKBicQJCQk8/PDDQ66ofD4fCoWCRYsW8cknn0zfIsfJhg0bWLJkCYmJiTz55JMolcphdk3Tgcfjoba2ltraWuLi4jAajWNugoeqEpSQ/KavA/tB/f39WK1W2tvb/XtZEVxlj0U4e1jBhuNx/ipFScTV4qKhsQFvf79/bIlWh0qlQlAIiEoF7r4+LBYLvb19mM2mEYtoZlraLxI6OjrYtWsXPp+PkpISMjIyaG9vx2q10tzcjMFgwGQyRVSVJ0kSO3fu5P777+ff//435513HitWrGDu3LmHnEgdyHPPPcd1111HW1vbmMdeeeWVVFRU8NFHHw25/Re/+AWzZ89GqVTyxhtvsGXLlojWIEdWUUAURdxuN3fccQeXXHLJkPsOO+ww1qxZww9/+MNpWt3EOOqoo9i0aRMrVqzgpJNO4vbbb+dnP/sZlZX+woXS0tIpdRXo7u7GZrPR2NhIenp6RPsLwyMsyV+4MCizGRMTw+zZs3G5/EMeXa6WqEVZo0VYkuTPyR/ojBEuoujD6Wyi0d6IgEB2dqCyb9BIDlFCkHzExcdTXFxMU1Mz+/btIy0tDaPROCQane5qv4miVqs56qijqKmpYfPmzahUKrxeL7m5uRx33HERfWclSeKbb75h9erV/L//9//49a9/zfbt2yksLDzkRWo8tLe3k5GRMeS2Z599lurqal588UX+9Kc/jetxD85v4jQSaiLxJ598wnvvvYd+YDzCgeTn52M2m6dhtdEhISGBBx98kB/96EcsW7aM//znPzzyyCN0d3ezfv16iouLJ3V4niRJtLW1DYiHC71eH3HqJkBAsJwNrUj94ogBTEaGhpQUNVarle3btmE0RifKknwSCoWIqBgkWNJAtd84Rnr0e/tx2B04HA5i42Ix5ueTnpExsheiBILXB0olWm0WaWlpWK1Wtm3dhtFkRKPRDFT7qcMqYZ+pBNwmnE4nCoUCpVKJKIqo1eqwKwZFUeSzzz5j1apVbNiwgUsuuYTHH3+cvLy8SV79wcuXX37Jq6++yjvvvBO8bc+ePaxYsYLPPvtsQlWRslhFiNPp5KKLLhoykfi9997jtNNOm+6lTSqCIHDKKaewdetWrrnmGo4//nhWrVrFySefHIyyom3XJIoiTqcTm81GT08Pubm5lJSUTDiSS1YngCThrHWNWvgwWVGWJEooGBAsAJ8v4gKM/SPjnahT1MyeXUiKWh2eYa+EfyijUkFsbAxFRbNpaXFhs1nx0UOued5BK1SiKOJwOLBarXg8HoxG48DQSiVOp5PKykoaGhooKSkZMQUoiiLvvvsu999/P1VVVfz2t7/l1VdfPaidXQazYsUK7r333lGPqaiooLi4OKLH3bFjB+eeey633XYbp59+OuDfBvnlL3/JHXfcQVFR0bjXDPKelcw4kCSJf/3rX1x++eVB0XI6nVGza/J6vdTX11NTU4MgCOTn55OdnR31XpWu9p4xBStAYC+ro6M9SlGWNDDTQwAp/Mfp7u6mobGBVpeLjAwN2dkGEhPHV+wiCCAplSBAbJyKjKxkrLZqHA7HtO9JRorP5wu6TQDBsfEHFlcMHjd/4DBSr9fL66+/zv3334/dbg9aIoWqgjuYaWpqoqWlZdRjCgoKhlx4jrVntWvXLr7//e9zySWXcNdddwVvb2trIz09fcjnIIoikiShVCp5//33Ofnkk8NatyxWMuPGbrdz6aWXsnHjRh555BHmz59PVVUVer1+XHZNg4c/JiYmYjKZyMrKmtQS4EgEC8DlasFisZCSkjKBKEsCUUQSRQSFAkmhGDUikpDoaO+gsbGRjs4OtFlaDAbDhBpggwgCKZokMnWpwWiqpaWFXbt2ER8fT2lp6Yyp/AyF1+ulrq4Om81GTEwMZrM5rIGhbW1tfPHFF9x5553cfvvtOBwOHnjgAdxud9ASaSa/7qlmNLHauXMnJ598MosXL+a+++4bcp8oiuzatWvIbY8//jgfffQRr732GmazOez3WRYrmQkhiiLPPvssy5cv57zzzuMPf/gDNTU1Edk1dXZ2YrPZcDgcaDQajEbjlA5/jFSwJhJlCUiIXu/Q2xQKUCg4sExdQgpW9nncHnQ6XVhehuEiKASystNISR9+svB6vezbt4+6urphEchMIFANWlNTQ1JSUvDCJpLvjMvl4le/+hXr1q0jNTWVP/7xj/zmN7+JzkXAIUJNTQ0ul4s333yTVatW8dlnnwFQWFhIcnIyO3bs4OSTT+aMM85g1apVwb9TKpUjZlhuv/32cVUDymIlExWqq6tZunQpNTU1PP300+Tk5LBv3z7y8/OZNWtWyPHdLS0t2Gx+y6Ps7Gzy8/On7Wo2UsGCSKMs/3gR0Re64XiwYImij6Ymv7GshIRBb0CrzRpS2TdRYuNj0OVnEBs3uvAFRs0rFApKS0tHnH47VfT19VFTU0NdXR2pqanBsfGRiFR7e3vQEkmv17N06VLefvttKisreeSRR/if//mfgyb9OdksWbKE559/ftjtH3/8cbA6+I477hh2v9FoDKZkD0QWK5lpx+fzsWbNGm677TYuu+wyrr/+evbu3YskSUG7JlEUsdvt2Gw23G43eXl55OXlzQiDz862HprqIhOs8KIsCUTfmNV+PlHE7mzC6XSgiokh25BNhiYj5ADIiZCSnkhmdlrYkZIoilRXV2Oz2cjPz6egoGDKvSJ7enqwWq00NjaSmZmJyWQaMl4jHJqbm4OWSMXFxaxcuZIf/OAHKBQKJEnixRdf5IUXXuDdd9+VvfxmILJYyUSd7du3c9FFF+H1ennqqadISUlh+/btpKWlBcuIjUZjyA3w6WY8ggWDoiy1GpNpv5N7qLTfgXjcHhrtjTidTSSnJJOdm0vqgOFuNBkt7RcOnZ2d7Nq1C6/XS2lp6ZQ48nd2dmK1WnE6neh0OkwmU8hJxaNRX1/Pww8/zLPPPsvRRx/NLbfcwkknnTSj0poyYyOLlcyk4PF4uP3223nggQcoKSmhsrKSJUuW8JOf/IT58+fP6M3r8QrW0CjLSKYmA8k3cpNvb08vDY0NuFpcpKWlYRgYGT/SHtZEiIlTocvXEBc/sf0uURSpqalh3759ZGdnM3v27EmJQtra2rBYLLhcLrKzszGZTBGNjZckierqatasWcPLL7/MaaedxsqVKznmmGPkFN9BiixWMpPChg0buP/++3n99deJjY0lPz+fl156CVEUaWhomPGl0eMVLABXSwuWfXtJSU7BZDIRM2jSriRBV2cnDY0NdLT7R8brDQYSEob2jkVTsJLTEsnKCT/tFw49PT3s2rWL3t5eiouLo9KDJEkSLpcLi8VCR0dHcGx8JAUPkiRRUVHB6tWreeONN/if//kfVqxYQXl5+Yz9rsmEhxwHy0SdTz/9lFNOOQWDwUBVVRV2u50TTzyRRYsW8fnnn1NeXo7FYmHz5s309fVN93JDkpKWSFZuRsSjPQQk0lNTOeywchAEtm3fRnNzM5Io0epqZdeunVTtriIxIZH58+djLjAPEyoASRRBFJmI5bqgEMjKSUeXlxH1lFdiYiILFizAbDazY8cOtm/fjsfjGddjBRzzN2zYwPbt28nIyGDRokXMnj07bKEKWCL94he/4Pjjjyc5OZlt27bx0ksvMW/ePFmoDgFksZrBPPHEE5SXl6NWq1Gr1SxcuJB33313yDHr16/n5JNPJikpCbVazQknnEBvb+80rdjP8ccfT21tLQ8++CBms5nk5GQef/xx/vGPf3Dvvfdy6aWX+vd1YmNZv349jY2N07rekYhMsCQESRzYn5KIiVExe3YhRqMRi8XKN5s2YbFYyEjP4PDDDycvP29IxBXyEScgWDFxKnJmaVFnTF66NTBPauHChfh8Pr788kvsdjvhJmsCUfb69euprKxEr9ezaNEiCgoKhvgUjvUYn376KT/60Y8466yzMJvN7N69m7/85S8UFRUd9CIVjREd//rXvzjttNPIysoKnkfee++9KXoF0UMWqxlMbm4u99xzD5s2beKbb77h5JNP5txzz2Xnzp2AX6jOPPNMTj/9dDZs2MDGjRu56qqrpn3jWKFQDPthCYLAWWedxbZt28jIyODYY4+lsrKS0tJSqqqq2LZt27ivzCeT8ATL3+Q7uCzd6/XS2NBIja2G2NgYEhLiESWR2LjYiErQxyNYyWmJ5BZqJ7w/FS7x8fHMmzeP4uJiKisr2bJly6gRs8/no7a2li+++ILq6mqMRiPHH388RqMx7IKbgCXSaaedxi9+8QuOOuooLBYLDz/8MPn5+dF6adNOYETHFVdcEfL+wSM6du7cyS233MLKlSt59NFHg8d8+umnnHbaafznP/9h06ZNfP/73+eHP/zhQTfKSN6zOsjIyMhg1apVXHzxxRxzzDGcdtpp3HnnndO9rIiQJIlXXnmFK6+8ktNOO40///nPfneGjg7KysrIzMyc7iUOY+Q9LAnJ6yMgJv0DI+MdTgeJCYkYsrMHGpzB1eLCYrWgTlEP28saC0EhgFI5qjWToBDQ6FNJ1URWLRdNPB4Pu3fvpqmpadjUXq/XG2zkjY2NDbpNRBL9eL1e/v3vf7N69WoaGhq49tprueqqqw45S6QDicaIjsGUlZVx/vnn84c//CGKq5xc5MjqIMHn8/HKK6/Q3d3NwoULcTqdfP3112i1Wo499lh0Oh0nnngin3/++XQvdUwEQeCCCy5g27ZttLe3s2jRIpqbmyksLGTbtm3B8uiZxPAISwJJRBpI+/X29mGptrBlyxZ6e3uZM6eY0rJS0tPTgn+TocmgvHxecC+rpaUl7AIOSZTA5xvwExxOTKyKnIKsaRUqgNjYWObOncthhx2GxWJh06ZNtLW1sXfvXj777DOam5spLS3lmGOOicip3+Px8MILL3DkkUfy+9//niVLlmCxWLj11lsPeaGKlFAjOgYjiiKdnZ2jHjMTkTvfZjjbt29n4cKF9PX1kZyczOuvv05paSlfffUV4O8GX716NfPnz+eFF17glFNOYceOHcyePXuaVz42ubm5/Oc//+Gpp57iV7/6Fb/85S+55ZZbsFqtfPXVV8ydO3dGnYhS0vwu3c46F/j83n6dnV3YGxtpa2tDo9Ewd+5cEhJHLrEO7GUFoixXiyvsKCswjwrV0AgrKTWBrJx0lMqZc+2ZmZnJ4Ycfzvbt29m4cSOJiYmUl5ej0Wgiepyenh5eeOEFHnroIWJjY7nxxhtZvHixbIk0AqFGdBzI6tWr6erq4uc///kUrmzizJxvt0xI5syZw5YtW/j666+54oorWLx4Mbt27UIU/f07v/nNb1i6dCmHH344a9asYc6cOfz1r3+d5lWHj0Kh4IorrmDTpk1s376dU045JTgkb9OmTezZsyf4WmcCKWmJZBlSaXW52LVzF5WVlcTFxTFv3jwKZhWMKlSDGW+UJUkSeP0RliBAZnYa+nzNjBKq7u5udu7cyddff01iYiKlpaWAf65RZ2dnWI/R0dHB/fffT1lZGc8++yx33303FRUVXHbZZQe9UK1YsQJBEEb9r7KyMuLHDTWi40Beeukl7rjjDv7xj3+g1Won+lKmFDmymuHExsZSWFgIwIIFC9i4cSMPPfQQK1asAAieCAKUlJRQU1Mz5eucKEVFRXz66afce++9/OAHP+Dqq6/m6quvZvfu3TQ3NwftmqaTwVZR7d2dpKWlUTQncnf5AOONsiRJIlahQGfOIi5h+m2qAnR0dGC1WmlqakKv13PMMccEm7/1ej0Wi4UNGzZgNBopKCgIWQjU3NzM448/zlNPPUVRURFPPfUUP/rRj6a9aCia3HDDDSxZsmTUYwoKCiJ6zF27dnHKKadw2WWXceutt4Y85pVXXuGSSy5h7dq1nHrqqRE9/kxAFquDDFEUcbvdmEwmsrOzqaqqGnL/7t27Oeuss6ZpdRNDpVJxyy23cNZZZ7F48WLee+89nn76aeLj49mwYQMFBQWYTKYpL0c+cL6WyWTiqKMM9LT34rA1TfjxMzQZpKj9U4m3bd+GyWQiI0MzYgViUmoiWmPWjImmWltbsVgstLa2kpOTw7HHHjvMbUKpVFJYWIhOp2Pnzp1B+6RZs2YB0NjYyIMPPsizzz7LUUcdxdq1azn55JMPKZEKkJWVFdVBjoNHdAyeJTWYl19+mWXLlvHKK69wzjnnRO25pxJZrGYwK1eu5KyzziI/P5/Ozk5eeuklPvnkE9577z0EQeDGG2/ktttuY968ecyfP5/nn3+eyspKXnvttele+oQ44ogj2LhxI7feeivf//73ufXWW/n1r39NRUUFTU1NzJ07d8Qpr9HE4/FQU1NDbW0tiYmJFBUVodVqg2KZkuEvZoiGYIWMssxmYmL2/0QFQUCTnUGadnqdz2G/a77FYqGrq4u8vDzmzp07piFxSkoKRx11FFVVVSxatIjjjz+e9PR0XnvtNU499VTee+89jj322IO+PypaBEZ01NTU4PP5gk7loUZ0LF++HLvdDgwd0fHSSy+xePFiHnroIY4++ujgMQkJCRGbAU8ncun6DObiiy/mww8/pLGxkdTUVMrLy7n55ps57bTTgsfcc889PPbYY7hcLubNm8d9993H8ccfP42rjh6SJLFu3TqWLVtGbm4ujz32GP39/ZNu19TT04PNZqOhoYH09HRMJtOoYyg6XV1REawA/f3eoMdgIMqKiVWhN2uJT5re/RpJkoJj4/v6+oJj48Nt4g08RkVFBbfeeivvv/8+CQkJ3Hffffz2t7+VReoAojGi46STTmLdunXDjlm8eDHPPfdctJc8achiJTPj6ejoYPny5axdu5Z7772Xs846i4qKCpKTkyktLSU+frhd0XifJ7DnotVqMZlMYe+TRVuwYH9fltaQxTEnHx3SlmmqEEUxODZeFEWMRiM5OTkRueZLksS3337LqlWreP/997nwwgv53e9+x7p167j55pv58Y9/zGOPPRaxq7rMdwNZrGQOCiRJ4q233uKyyy7je9/7Hg888ACtra00NTVRUlKCXq8f9+O6XC6sVittbW3k5ORgNBojcvgOEG3BEgSBlMxkGlvqaW1tpbi4eNyvc7z4fD7q6+uxWq0olUrMZjN6vT6ivSRJkvj8889ZtWoV69evZ+nSpdx4440YjcbgMXV1dTz88MP8+c9/nnFjY2RmBrJYyRxUNDU1cfnll/Ppp5/yyCOPcNRRR1FZWUlGRgYlJSUReco5nc5gOitaQyA7Wrpw1kxcsFQxQ9N+DoeDiooK0tPTKSkpmfRhlf39/UG3ifj4eMxm85D9unAQRZEPPviAVatWsXPnTi6//HKWL1+OTqebxJXLHKrIYiVz0CGKIi+++CLXXnstP/jBD7jzzjupr68Py67J5/PR0NCAzWZDkqRxpbPGYqKClaRORGvMRKkauiaPx0NFRcWkRllutztYVKJWqzGbzWRkZEQkUj6fL2iJVFdXxzXXXMPVV189JcMaZQ5dZLGSOWix2WwsXbqUffv28cQTT1BYWMju3bvR6/UUFQ3tf/J4PNTV1QUjBaPRiE6nm7TS6PEIliAIaAzppOlGr9Cy2+1UVlZGNcrq7e3FarXS0NBARkYGZrM5YvcQj8fDq6++ygMPPEBXVxfLly/nN7/5jbwHJRMVZLGSOajx+Xw8+uij3HLLLSxdupSbb76Zffv24Xa7mTt3LnFxcdTU1FBfX09qaupAdV1kkcJ4iUSwVDEqdKYsEpLDK6KIVpTV1dWF1WrF4XCQlZWF2WyOuPm6t7c3aImkVCq58cYbWbJkSdQKX2RkQLZbkjnIUSqVXHvttWzYsIGvvvqK0047DYVCQVtbGzfddBOff/45fX19LFiwgAULFqDRaKasPFqtSUabP3bzZ5I6kbzi7LCFCvzOJoPHcmzdujWiESvt7e1s3bqVr7/+GoVCwcKFCykvL49IqDo6OlizZg1lZWX85S9/4c4776SyspLLL7/8kBGqaMyTAvjkk0844ogjiIuLo7Cw8KAqGZ8pyE3BMocEpaWlfPHFF1x22WWcdNJJCILAOeecQ2xsLD09PdPmhKAecEEPFWEJgkCGIY10Xdq4H1+v15ORkUFFRQVffvklJSUlIxYwSJIUdJtob28nJyeH4447LmJhaWlp4YknngimXh9//HHOPffcQ7KKLzBPauHChTzzzDPD7h88TyovL48vv/ySyy67DKVSyVVXXQWAxWLhnHPO4fLLL+fvf/87H374IZdccgkGg4Ezzjhjql/SQYucBpQ5JHjjjTf485//zO7duzn33HP5/PPPSU9P56mnnkKlUmGz2abNrgmGpwRVMUp0Jm1E0dRYjLSXJUkSzc3NWCwWuru7yc/PH1flo91u56GHHuKvf/0rCxYs4Pe//z2nnnrqIWmJdCATmSd18803884777Bjx47gMb/4xS9oa2vjv//972Qt+ZDj0P+WyYTFE088QXl5OWq1Ojj6+t133w3eb7fb+fWvf41erycpKYkjjjiCf/7zn9O44qH8v//3/zj//POpqanhueeeY+vWrRx77LGccMIJfPDBBxxxxBE0NDSwceNGenp6pnx9g1OCiSkJ5BXnRFWowB9lHXvssQDBEfONjY189dVX7Nq1C61Wy6JFi5g1a1bYQiVJEhaLhWuvvZaysjL27t3Lu+++y8cff8zpp5/+nRCqSDlwntT69euHGceeccYZrF+/fqqXdlAjpwFlAP9sqXvuuYfZs2cjSRLPP/885557Lps3b6asrIyLLrqItrY23nzzTTIzM3nppZf4+c9/zjfffMPhhx8+3csfMsYbICkpiQcffJAf/ehHLF26lHfeeYdHH32Uvr4+vvrqK4qKioZMsZ0K1JpkYuNjJtUyKTD8sKqqiu3bt6NQKJg1axZ5eXkRu01UVlbywAMP8M9//pMf/ehHfPHFFxx++OGyJdIohJonZbfbh6VmdTodHR0d9Pb2jqsB/buIfFkkA8APf/hDzj77bGbPnk1RURF33XUXycnJwSGPX375JVdffTVHHXUUBQUFwQmtmzZtmuaVj4wgCJxyyils3bo1uD+zefNmDjvsMKqrq9m8eTN9fX1TuqbJFCqv1+8p+Pnnn9PW1kZxcTEajQar1Upzc3NYjyFJEps3b+bCCy/kuOOOIzY2li1btvDqq69yxBFHHBJCNZ3zpGTGjxxZyQzD5/Oxdu1auru7WbhwIQDHHnssr776Kueccw5paWn84x//oK+vj5NOOml6FxsG6enpvPDCC/zzn//kiiuuYNGiRaxevZrm5mbWr18/IbummYDH46G2tpba2tpgRVpWVhaCIJCbmxt0v3A4HBQXF4dMAUqSxBdffMHq1av5/PPPWbp0KZWVlZhMpql/QZPMVM+T0uv1OByOIbc5HA7UarUcVUWALFYyQbZv387ChQvp6+sjOTmZ119/PTjc8R//+Afnn38+Go0GlUpFYmIir7/+enAw5ExHEAR++tOfcvzxx3PppZdy7LHH8uijj3LEEUdQWVmJ0+mMyK5pJtDX10dNTQ11dXVBV/4D3eEFQRhWMVhQUEB+fj7gdwP5f//v/7F69Wq2b9/Ob37zG1544YWDWrzHYqrnSS1cuJD//Oc/Q2774IMPgheCMuEhVwPKBAnMb2pvb+e1117jL3/5C+vWraO0tJSrr76aDRs2cPfdd5OZmckbb7zBmjVr+OyzzzjssMOme+kRIYoif/3rX7nhhhs477zzuP3226mtrQ3Lrmkm0NPTg9VqpbGxEY1Gg9lsDmsuUWC8x8UXX4xCoeDHP/4xf/3rX6mpqQlaIg0uDJDZP0/qzTffZNWqVXz22WdA6HlSq1atCv7d4HlSFouFuXPncuWVV7Js2TI++ugjrrnmGt555x25dD0CZLGSGZFTTz2VWbNmcdNNN1FYWMiOHTsoKysbcn9hYSFPPvnkNK5y/FRXV7N06VJqamp4+umnMRqN7N69G4PBwOzZs8c9rn6y6OzsDLpN6PV6TCZTxFZG/f39PPnkk/zxj3+kr6+PCy+8kMceeyxi14rvCtGYJwX+puDrr7+eXbt2kZuby//+7/+OmYqUGYosVjIjcvLJJ5Ofn88NN9xAeXk5u3btoqSkJHj/GWecgdFo5Omnn57GVU4Mn8/HAw88wO23385vfvMbbrjhBvbu3Ru0a4rUH28yaGtrw2Kx4HK5yM7OxmQyRbzX0dvby9/+9jceeughBEHgd7/7HcnJySxfvpxTTjmFRx99NKqpMRmZaCOLlQwAK1eu5KyzziI/P5/Ozk5eeukl7r33Xt577z1OOukkSktLMRgMrF69Go1GwxtvvMGNN97I22+/zdlnnz3dy58w27Zt46KLLsLn8/H000+TmprKvn37yM/PZ9asWVPeTxSYs2WxWOjo6CA3Nxej0UhcXGTVhJ2dnTzzzDM88sgjpKens2LFCi644ILg3pzD4eCqq67id7/7HUcfffRkvBQZmaggi5UMABdffDEffvghjY2Nwc36m2++mdNOOw2APXv2sGLFCj7//HO6urooLCzkd7/7Hb/+9a+neeXRw+12c8cdd/DQQw+xYsUKLr74YiorK5Ekiblz505JqkySJJqamrBYLPT29gbdJiIt/HC5XEFLpIKCAlauXMmPf/zjQ9ISSea7gSxWMjKDkCSJL7/8kiVLlpCZmcmTTz6JIAiTbtckiiJ2ux2r1YrX68VoNJKbmxuxuNjtdh5++GGeeeYZjjjiCFauXCk7TcgcEsjfYBmZQQiCEGwenj9/PosWLWLdunVBu6ZvvvkmqnZNPp+P2tpavvjiC6qrq8nPz+f444/HaDSGLVSSJGG1WrnuuuuC7hXvvPMOn3zyCWeeeaYsVDKHBHJkJSMzApIk8e6773LppZdy2GGH8cgjj9DZ2UlDQ8OE7Zq8Xm9wbHxsbCxmsxmdThfR40mSRFVVFQ888ACvvfYaP/jBD1ixYgULFiw4JJwmZGQGI19yyciMgCAInH322Wzbto20tDSOOeYYdu7cSXl5+bjtmjweD3v37uWzzz6jqamJ0tJSjjnmGPR6fdgCI0kSW7Zs4Ve/+hXHHnssSqWSzZs3s3btWo488shDRqjGmiUFcM0117BgwQLi4uKYP39+yGPee+89jjnmGFJSUsjKyuK8884bUlYuc3Agi5WMzBhoNBpefvllHnnkEa699lpuvPHGoG3R+vXrsdvtYz5GX18fVVVVfPbZZ3R0dDB//ny+973vBW2RwiGwn/aTn/yEU089Fb1eT0VFBc899xwlJSWHjEgFCMySuuKKK0Y9btmyZZx//vkh77NYLJx77rmcfPLJbNmyhffee4/m5mZ+8pOfTMaSZSYROQ0oIxMBdXV1XHzxxezYsYMnn3ySsrIyKisr0Wg0FBcXD6va6+7uxmq1YrfbyczMxGw2o1arI3pOURT56KOPWLVqFVu3buWyyy5j+fLlZGdnR/OlzVjCmSV1++2388Ybb7Bly5Yht7/22mtccMEFuN3u4N7dW2+9xbnnnovb7T6o7LW+68iRlYxMBOTm5vLuu+9yyy238Mtf/pL77ruP8vJyvF4v69evD7qbd3Z2sm3btqBr/THHHMO8efMiEiqfz8e///1vTjzxRJYsWcLJJ5+MxWJh9erV3xmhmigLFixAoVDw7LPP4vP5aG9v529/+xunnnqqLFQHGbJYychEiEKh4Le//S2bNm1i27ZtfP/738fj8VBQUMDLL7/MO++8w4YNG4iNjeXYY4+lrKyMpKSksB+/v7+fl156iaOPPprly5dz/vnnY7VaueOOO9BoNJP4yg49zGYz77//Pr///e+Ji4sjLS2Nuro6/vGPf0z30mQiRBYrGZlxUlRUxKeffsrixYs566yzOOGEE/jjH//I3r17iY2NRa/XR2SL1NfXx1/+8hfmz5/PXXfdxZVXXkl1dTU33XRTxKnDmcpkzZIaCbvdzqWXXsrixYvZuHEj69atIzY2lp/+9KfIOyAHFzPLqVNG5iDC5/Pxxhtv8K9//YvExER8Ph8FBQWceuqpJCUlsWnTprDsmrq6uoKWSKmpqdx2221ceOGFh2SaajJmSY3GY489RmpqKvfdd1/wthdffJG8vDy+/vprjjnmmKg9l8zkIkdWMjOCe+65B0EQuO6664K39fX1ceWVV6LRaEhOTua8884bNsRuOnnmmWdYvnw5S5cupa6ujtraWs444wxOOukk3nzzTY488khaWlr4+uuv6ezsHPb3ra2t/PnPf6akpIS1a9fy0EMPsWPHDpYsWXJIChX4Z0kVFxeP+l+o4ZDjpaenZ9iFQqDZWhTFqD2PzOQji5XMtLNx40aeeuopysvLh9x+/fXX89Zbb7F27VrWrVtHQ0PDjCo5vuiii9i7dy9XX301iYmJxMfHs2rVKt555x2eeuopzj//fLRaLVlZWaxbt467774br9eL3W7n1ltvpaSkhHXr1vG3v/2Nb775hp/97Geyd98gampq2LJlCzU1Nfh8PrZs2cKWLVvo6uoKHrN37162bNmC3W6nt7c3eIzH4wHgnHPOYePGjfzxj39kz549fPvttyxduhSj0cjhhx8+XS9NZjxIMjLTSGdnpzR79mzpgw8+kE488UTp2muvlSRJktra2qSYmBhp7dq1wWMrKiokQFq/fv00rTZ82trapIsvvlhSq9XSE088Ia1bt07S6/WSRqOR4uLipNNPP1365JNPJFEUp3upM5bFixdLwLD/Pv744+AxJ554YshjLBZL8JiXX35ZOvzww6WkpCQpKytL+tGPfiRVVFRM/QuSmRByn5XMtLJ48WIyMjJYs2YNJ510EvPnz+fBBx/ko48+4pRTTqG1tXWIe4HRaOS6667j+uuvn75Fh4kkSbz55ptceumlxMfHY7fbycnJwel08sADD3DZZZcdco28MjKThZwGlJk2XnnlFb799lv+/Oc/D7vPbrcTGxs7zGZHp9OF5RgxExAEgXPPPZetW7ei1Wr5+uuvqa6u5vXXX+fOO+88pMaryMhMNnI1oMy0UFtby7XXXssHH3xAfHz8dC9nUjEYDHzzzTfBf59++uls376dXbt2TeOqZGQOLuTISmZa2LRpE06nkyOOOAKVSoVKpWLdunU8/PDDqFQqdDodHo9nmMWOw+FAr9dPz6KjSHp6Oscdd9x0L0NG5qBBjqxkpoVTTjmF7du3D7lt6dKlFBcXc/PNNwen43744Yecd955AFRVVVFTU8PChQunY8kyMjLTiCxWMtNCSkoKc+fOHXJbUlISGo0mePvFF1/M8uXLycjIQK1Wc/XVV7Nw4UK5kVNG5juInAaUmbGsWbOGH/zgB5x33nmccMIJ6PV6/vWvf033sr4TRGuWlCRJrF69mqKiIuLi4sjJyeGuu+6avIXLHLLIpesyMjLDuO2224Kmr88880zI8RzXXHMNc+bM4euvv2bbtm3DxnMEjnn//fe57777OOyww3C5XLhcLk477bTJfxEyhxSyWMnIyIzIRGZJVVRUUF5ezo4dO5gzZ87kLlTmkEdOA8rIyEwKb731FgUFBbz99tuYzWZMJhOXXHIJLpdrupcmcxAii5WMjMykUF1djc1mY+3atbzwwgs899xzbNq0iZ/+9KfTvTSZgxBZrGRkviNM9SwpURRxu9288MILLFq0iJNOOolnnnmGjz/+mKqqqqg9j8x3A7l0XUbmO8JUz5IyGAyoVCqKioqCt5WUlAB+R3V5H0smEmSxkpH5jpCVlUVWVtaUPd9xxx2H1+tl3759zJo1C4Ddu3cDfkNiGZlIkMVKRkZmGDU1NbhcriGzpAAKCwtJTk4G/LOkurq6hsySAigtLSU2NpZTTz2VI444gmXLlvHggw8iiiJXXnklp5122pBoS0YmHOTSdRkZmWEsWbKE559/ftjtH3/8MSeddBIAJ510EuvWrRt2jMViwWQyAdDQ0MDVV1/N+++/T1JSEmeddRb3338/GRkZk7l8mUMQWaxkZGRkZGY8cjWgjIyMjMyMRxYrme8s99xzD4IgcN111wHgcrm4+uqrmTNnDgkJCeTn53PNNdfQ3t4+vQuVkZGRCyxkvpts3LiRp556ivLy8uBtDQ0NNDQ0sHr1akpLS7HZbFx++eU0NDTw2muvTeNqZWRk5D0rme8cXV1dHHHEETz++OP86U9/Yv78+Tz44IMhj127di2/+tWv6O7uRqWSr+1kZKYLOQ0o853jyiuv5JxzzuHUU08d89j29nbUarUsVDIy04z8C5T5TvHKK6/w7bffsnHjxjGPbW5u5s477+Syyy6bgpXJyMiMhhxZyXxnqK2t5dprr+Xvf/878fHxox7b0dHBOeecQ2lpKbfffvuUrC9aAw8D7N27l5SUlBEfS0bmYEIWK5nvDJs2bcLpdHLEEUegUqlQqVSsW7eOhx9+GJVKhc/nA6Czs5MzzzyTlJQUXn/9dWJiYqZkfR6Ph5/97GdcccUVox63bNkyzj///FGP6e/v54ILLmDRokXRXKKMzLQhpwFlvjOccsopbN++fchtS5cupbi4mJtvvhmlUklHRwdnnHEGcXFxvPnmm2NGYNHkjjvuAPwDD0fi4YcfBqCpqYlt27aNeNytt95KcXExp5xyCl9++WVU1ykjMx3IYiXznSElJYW5c+cOuS0pKQmNRsPcuXPp6Ojg9NNPp6enhxdffJGOjg46OjoAvwmsUqmcjmVHzEcffcTatWvZsmUL//rXv6Z7OTIyUUEWKxmZAb799lu+/vprwG/YOpjBfnczmZaWFpYsWcKLL76IWq2e7uXIyEQNec9K5jvNJ598EuyxOumkk5AkKeR/4xWqqR54eOmll/LLX/6SE044IWqPKSMzE5AjKxmZSWSqBx5+9NFHvPnmm6xevRoASZIQRRGVSsXTTz/NsmXLovZcMjJTiSxWMjKTyFQPPFy/fn2wqhHg3//+N/feey9ffvklOTk5U7YOGZloI4uVjMwMIRoDDwNj4wN88803KBSKYYUlMjIHG7JYycjMEP7whz8MGXh4+OGHA0MHHl5yySVDBh4GjjlYCkBkZMaLbGQrIyMjIzPjkasBZWRkZGRmPLJYycjIyMjMeGSxkpGRkZGZ8chiJSMjIyMz45HFSkZGRkZmxiOLlYyMjIzMjEcWKxkZGRmZGY8sVjIyMjIyMx5ZrGRkZGRkZjyyWMnIyMjIzHhksZKRkZGRmfHIYiUjIyMjM+P5/0nqCVGmGOodAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "ax.scatter(X_test[:, 0], X_test[:, 1], y_pred, alpha=0.3)\n",
    "ax.view_init(30, 50)\n",
    "x1_range = np.linspace(X_test[:, 0].min(), X_test[:, 0].max(), 10)\n",
    "x2_range = np.linspace(X_test[:, 1].min(), X_test[:, 1].max(), 10)\n",
    "X1_grid, X2_grid = np.meshgrid(x1_range, x2_range)\n",
    "\n",
    "intercept = model.intercept_\n",
    "coef1, coef2 = model.coef_[0], model.coef_[1]\n",
    "Z = intercept + coef1 * X1_grid + coef2 * X2_grid\n",
    "ax.plot_surface(X1_grid, X2_grid, Z, cmap='viridis', alpha=0.2)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "ec090c13",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 47700.,  45800., 500001., ..., 500001.,  72300., 151500.],\n",
       "      shape=(4128,))"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "4ca0b4f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 55838.69584616, 184800.31785128, 335265.62958912, ...,\n",
       "       439171.75394177, 130418.50686554, 175269.66836557], shape=(4128,))"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4d33b98",
   "metadata": {},
   "source": [
    "## 模型评估"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "f71883b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "系数\t[-4.26226944e+04 -4.24410116e+04  1.18296423e+03 -8.18887824e+00\n",
      "  1.16246555e+02 -3.84926063e+01  4.63652583e+01  4.05389240e+04]\n",
      "截距\t-3577395.06758456\n",
      "R2评估\t0.6246548053727379\n",
      "MSE\t4918557129.791423\n"
     ]
    }
   ],
   "source": [
    "print(f'系数\\t{model.coef_}')\n",
    "print(f'截距\\t{model.intercept_}')\n",
    "print(f'R2评估\\t{model.score(X_test, y_test)}')\n",
    "\n",
    "mse = mean_squared_error(y_test, y_pred)\n",
    "\n",
    "print(f'MSE\\t{mse}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de6bb2ec",
   "metadata": {},
   "source": [
    "## 网络搜索分析最优惩罚项系数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "13770ad8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "alphas = np.logspace(-2, 3, 20)\n",
    "\n",
    "train_scores, valid_scores = validation_curve(\n",
    "    Ridge(), X, y, param_name=\"alpha\", param_range=alphas, cv=5, scoring='r2'\n",
    ")\n",
    "\n",
    "# plt.subplot(2, 1, 1)\n",
    "plt.title('Validation Curve for Ridge(r2)')\n",
    "plt.semilogx(alphas, np.mean(train_scores, axis=1), label='Training score')\n",
    "plt.ylabel('Score')\n",
    "plt.legend()\n",
    "# plt.subplot(2, 1, 2)\n",
    "plt.semilogx(alphas, np.mean(valid_scores, axis=1), label='Validation score')\n",
    "plt.xlabel('Alpha (Regularization strength)')\n",
    "plt.ylabel('Score')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "c7baf2c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "alphas = np.logspace(-2, 3, 20)\n",
    "\n",
    "train_scores, valid_scores = validation_curve(\n",
    "    Ridge(), X, y, param_name=\"alpha\", param_range=alphas, cv=5, scoring='neg_mean_squared_error'\n",
    ")\n",
    "\n",
    "# plt.subplot(2, 1, 1)\n",
    "plt.title('Validation Curve for Lasso(-MSE)')\n",
    "plt.semilogx(alphas, np.mean(train_scores, axis=1), label='Training score')\n",
    "plt.ylabel('Score(train)')\n",
    "plt.legend()\n",
    "# plt.subplot(2, 1, 2)\n",
    "plt.semilogx(alphas, np.mean(valid_scores, axis=1), label='Validation score')\n",
    "plt.xlabel('Alpha (Regularization strength)')\n",
    "plt.ylabel('Score(test)')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "MCM",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
